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Model Card for Model ID

model.tar.gz/

|- pytorch_model.bin |- .... |- code/ |- inference.py |- requirements.txt

This modelcard aims to be a base template for new models. It has been generated using this raw template.

Model Details

from huggingface_hub import hf_hub_download hf_hub_download( repo_id="google/pegasus-xsum", filename="config.json", revision="4d33b01d79672f27f001f6abade33f22d993b151" )from huggingface_hub import hf_hub_download hf_hub_download(repo_id="google/pegasus-xsum", filename="config.json") )

Model Descriptionmodel.tar.gz/

|- pytorch_model.bin |- .... |- code/ |- inference.py |- requirements.txt

image/webp

  • Developed by: [More Information Needed]{"parquet_files":

image/png

[
    {"dataset": "codeparrot/codecomplex", "config": "default", "split": "train", "url": "https://huggingface.co/datasets/codeparrot/codecomplex/resolve/refs%2Fconvert%2Fparquet/default/train/0000.parquet", "filename": "0000.parquet", "size": 4115908}
],

"pending": [], "failed": [], "partial": false }

  • Funded by [optional]: [More Information Needed] import pandas as pd

url = "https://huggingface.co/datasets/codeparrot/codecomplex/resolve/refs%2Fconvert%2Fparquet/default/train/0000.parquet" df = pd.read_parquet(url) df.head(5)

  • Shared by [optional]: [More Information Needed] import requests headers = {"Authorization": f"Bearer {API_TOKEN}"} API_URL = "https://datasets-server.huggingface.co/is-valid?dataset=cornell-movie-review-data/rotten_tomatoes" def query(): response = requests.get(API_URL, headers=headers) return response.json() data = query()
  • Model type: [More Information Needed] { "viewer": true, "preview": true, "search": true, "filter": true, "statistics": true, }
  • Language(s) (NLP): [More Information Needed] { "viewer": true, "preview": true, "search": false, "filter": true, "statistics": true, }
  • License: [More Information Needed] { "viewer": true, "preview": true, "search": true, "filter": false, "statistics": true, }
  • Finetuned from model [optional]: [More Information Needed] { "viewer": true, "preview": true, "search": true, "filter": true, "statistics": false, }

Model Sources [optional]

image/png

  • Repository: [More Information Needed] df.groupby('complexity')['src'].apply(lambda x: x.str.len().mean()).sort_values(ascending=False).plot.barh(color="orange")
  • Paper [optional]: [More Information Needed] huggingface-cli login
  • Demo [optional]: [More Information Needed] roseteromeo56/romeo-rosete

Uses

python -m pip install huggingface_hub

huggingface-cli login

Direct Use

git clone https://huggingface.co//

cd git clone https://huggingface.co/datasets// cd git clone https://huggingface.co/datasets// cd git clone git@hf.co:/ cd git lfs install huggingface-cli lfs-enable-largefiles . # Create any files you like! Then... git add . git commit -m "First model version" # You can choose any descriptive message git push https://huggingface.co/docs/hub/repositories-getting-started [More Information Needed] { "viewer": false, "preview": true, "search": true, "filter": true, "statistics": true, }

Downstream Use [optional]

[More Information Needed] { "viewer": false, "preview": false, "search": false, "filter": false, "statistics": false, }

Out-of-Scope Use

[More Information Needed]import requests headers = {"Authorization": f"Bearer {API_TOKEN}"} API_URL = "https://datasets-server.huggingface.co/splits?dataset=ibm/duorc" def query(): response = requests.get(API_URL, headers=headers) return response.json() data = query()

Bias, Risks, and Limitations

[More Information Needed] { "splits": [ { "dataset": "ibm/duorc", "config": "ParaphraseRC", "split": "train" }, { "dataset": "ibm/duorc", "config": "ParaphraseRC", "split": "validation" }, { "dataset": "ibm/duorc", "config": "ParaphraseRC", "split": "test" }, { "dataset": "ibm/duorc", "config": "SelfRC", "split": "train" }, { "dataset": "ibm/duorc", "config": "SelfRC", "split": "validation" }, { "dataset": "ibm/duorc", "config": "SelfRC", "split": "test" } ], "pending": [], "failed": [] }

Recommendations

image/png

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

How to Get Started with the Model

Use the code below to get started with the model.

[More Information Needed] { "dataset_info": { "description": "", "citation": "", "homepage": "", "license": "", "features": { "plot_id": { "dtype": "string", "_type": "Value" }, "plot": { "dtype": "string", "_type": "Value" }, "title": { "dtype": "string", "_type": "Value" }, "question_id": { "dtype": "string", "_type": "Value" }, "question": { "dtype": "string", "_type": "Value" }, "answers": { "feature": { "dtype": "string", "_type": "Value" }, "_type": "Sequence" }, "no_answer": { "dtype": "bool", "_type": "Value" } }, "builder_name": "parquet", "dataset_name": "duorc", "config_name": "SelfRC", "version": { "version_str": "0.0.0", "major": 0, "minor": 0, "patch": 0 }, "splits": { "train": { "name": "train", "num_bytes": 248966361, "num_examples": 60721, "dataset_name": null }, "validation": { "name": "validation", "num_bytes": 56359392, "num_examples": 12961, "dataset_name": null }, "test": { "name": "test", "num_bytes": 51022318, "num_examples": 12559, "dataset_name": null } }, "download_size": 21001846, "dataset_size": 356348071 }, "partial": false } import requests headers = {"Authorization": f"Bearer {API_TOKEN}"} API_URL = "https://datasets-server.huggingface.co/info?dataset=ibm/duorc&config=SelfRC" def query(): response = requests.get(API_URL, headers=headers) return response.json() data = query()

Training Details

Training Data

[More Information Needed] import requests headers = {"Authorization": f"Bearer {API_TOKEN}"} API_URL = "https://datasets-server.huggingface.co/first-rows?dataset=ibm/duorc&config=SelfRC&split=train" def query(): response = requests.get(API_URL, headers=headers) return response.json() data = query()

Training Procedure

Preprocessing [optional]

[More Information Needed] { "dataset": "ibm/duorc", "config": "SelfRC", "split": "train", "features": [ { "feature_idx": 0, "name": "plot_id", "type": { "dtype": "string", "_type": "Value" } }, { "feature_idx": 1, "name": "plot", "type": { "dtype": "string", "_type": "Value" } }, { "feature_idx": 2, "name": "title", "type": { "dtype": "string", "_type": "Value" } }, { "feature_idx": 3, "name": "question_id", "type": { "dtype": "string", "_type": "Value" } }, { "feature_idx": 4, "name": "question", "type": { "dtype": "string", "_type": "Value" } }, { "feature_idx": 5, "name": "answers", "type": { "feature": { "dtype": "string", "_type": "Value" }, "_type": "Sequence" } }, { "feature_idx": 6, "name": "no_answer", "type": { "dtype": "bool", "_type": "Value" } } ], "rows": [ { "row_idx": 0, "row": { "plot_id": "/m/03vyhn", "plot": "200 years in the future, Mars has been colonized by a high-tech company.\nMelanie Ballard (Natasha Henstridge) arrives by train to a Mars mining camp which has cut all communication links with the company headquarters. She's not alone, as she is with a group of fellow police officers. They find the mining camp deserted except for a person in the prison, Desolation Williams (Ice Cube), who seems to laugh about them because they are all going to die. They were supposed to take Desolation to headquarters, but decide to explore first to find out what happened.They find a man inside an encapsulated mining car, who tells them not to open it. However, they do and he tries to kill them. One of the cops witnesses strange men with deep scarred and heavily tattooed faces killing the remaining survivors. The cops realise they need to leave the place fast.Desolation explains that the miners opened a kind of Martian construction in the soil which unleashed red dust. Those who breathed that dust became violent psychopaths who started to build weapons and kill the uninfected. They changed genetically, becoming distorted but much stronger.The cops and Desolation leave the prison with difficulty, and devise a plan to kill all the genetically modified ex-miners on the way out. However, the plan goes awry, and only Melanie and Desolation reach headquarters alive. Melanie realises that her bosses won't ever believe her. However, the red dust eventually arrives to headquarters, and Melanie and Desolation need to fight once again.", "title": "Ghosts of Mars", "question_id": "b440de7d-9c3f-841c-eaec-a14bdff950d1", "question": "How did the police arrive at the Mars mining camp?", "answers": ["They arrived by train."], "no_answer": false }, "truncated_cells": [] }, { "row_idx": 1, "row": { "plot_id": "/m/03vyhn", "plot": "200 years in the future, Mars has been colonized by a high-tech company.\nMelanie Ballard (Natasha Henstridge) arrives by train to a Mars mining camp which has cut all communication links with the company headquarters. She's not alone, as she is with a group of fellow police officers. They find the mining camp deserted except for a person in the prison, Desolation Williams (Ice Cube), who seems to laugh about them because they are all going to die. They were supposed to take Desolation to headquarters, but decide to explore first to find out what happened.They find a man inside an encapsulated mining car, who tells them not to open it. However, they do and he tries to kill them. One of the cops witnesses strange men with deep scarred and heavily tattooed faces killing the remaining survivors. The cops realise they need to leave the place fast.Desolation explains that the miners opened a kind of Martian construction in the soil which unleashed red dust. Those who breathed that dust became violent psychopaths who started to build weapons and kill the uninfected. They changed genetically, becoming distorted but much stronger.The cops and Desolation leave the prison with difficulty, and devise a plan to kill all the genetically modified ex-miners on the way out. However, the plan goes awry, and only Melanie and Desolation reach headquarters alive. Melanie realises that her bosses won't ever believe her. However, the red dust eventually arrives to headquarters, and Melanie and Desolation need to fight once again.", "title": "Ghosts of Mars", "question_id": "a9f95c0d-121f-3ca9-1595-d497dc8bc56c", "question": "Who has colonized Mars 200 years in the future?", "answers": [ "A high-tech company has colonized Mars 200 years in the future." ], "no_answer": false }, "truncated_cells": [] } ... ], "truncated": false }

Training Hyperparameters

  • Training regime: [More Information Needed]

Speeds, Sizes, Times [optional]

[More Information Needed] ... "rows": [ { { "row_idx":8, "row":{ "gem_id":"GEM-SciDuet-train-1#paper-954#slide-8", "paper_id":"954", "paper_title":"Incremental Syntactic Language Models for Phrase-based Translation", "paper_abstract":""This paper describes a novel technique for incorporating syntactic knowledge into phrasebased machi", "paper_content":"{"paper_content_id":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29", "paper_headers":"{"paper_header_number":["1","2","3","3.1","3.3","4","4.1","6","7"],"paper_header_content":["Introduc", "slide_id":"GEM-SciDuet-train-1#paper-954#slide-8", "slide_title":"Does an Incremental Syntactic LM Help Translation", "slide_content_text":""but will it make my BLEU score go up?\nMotivation Syntactic LM Decoder Integration Questions?\nMose", "target":""but will it make my BLEU score go up?\nMotivation Syntactic LM Decoder Integration Questions?\nMose", "references":[] }, "truncated_cells":[ "paper_abstract", "paper_content", "paper_headers", "slide_content_text", "target" ] }, { "row_idx":9, "row":{ "gem_id":"GEM-SciDuet-train-1#paper-954#slide-9", "paper_id":"954", "paper_title":"Incremental Syntactic Language Models for Phrase-based Translation", "paper_abstract":""This paper describes a novel technique for incorporating syntactic knowledge into phrasebased machi", "paper_content":"{"paper_content_id":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29", "paper_headers":"{"paper_header_number":["1","2","3","3.1","3.3","4","4.1","6","7"],"paper_header_content":["Introduc", "slide_id":"GEM-SciDuet-train-1#paper-954#slide-9", "slide_title":"Perplexity Results", "slide_content_text":""Language models trained on WSJ Treebank corpus\nMotivation Syntactic LM Decoder Integration Questio", "target":""Language models trained on WSJ Treebank corpus\nMotivation Syntactic LM Decoder Integration Questio", "references":[

        ]
     },
     "truncated_cells":[
        "paper_abstract",
        "paper_content",
        "paper_headers",
        "slide_content_text",
        "target"
     ]
  }
  "truncated_cells": ["target", "feat_dynamic_real"]
},

... ], truncated: true

Evaluation

Testing Data, Factors & Metrics

Testing Data

[More Information Needed] import requests headers = {"Authorization": f"Bearer {API_TOKEN}"} API_URL = "https://datasets-server.huggingface.co/rows?dataset=ibm/duorc&config=SelfRC&split=train&offset=150&length=10" def query(): response = requests.get(API_URL, headers=headers) return response.json() data = query()

Factors

[More Information Needed] // https://datasets-server.huggingface.co/rows?dataset=ibm/duorc&config=SelfRC&split=train&offset=150&length=2 { "features": [ { "feature_idx": 0, "name": "plot_id", "type": { "dtype": "string", "_type": "Value" } }, { "feature_idx": 1, "name": "plot", "type": { "dtype": "string", "_type": "Value" } }, { "feature_idx": 2, "name": "title", "type": { "dtype": "string", "_type": "Value" } }, { "feature_idx": 3, "name": "question_id", "type": { "dtype": "string", "_type": "Value" } }, { "feature_idx": 4, "name": "question", "type": { "dtype": "string", "_type": "Value" } }, { "feature_idx": 5, "name": "answers", "type": { "feature": { "dtype": "string", "_type": "Value" }, "_type": "Sequence" } }, { "feature_idx": 6, "name": "no_answer", "type": { "dtype": "bool", "_type": "Value" } } ], "rows": [ { "row_idx": 150, "row": { "plot_id": "/m/03wj_q", "plot": "The film is centered on Mortal Kombat, a fighting tournament between the representatives of the realms of Earth and Outworld conceived by the Elder Gods amid looming invasion of the Earth by Outworld. If the realm of Outworld wins Mortal Kombat ten consecutive times, its Emperor Shao Kahn will be able to invade and conquer the Earth realm.\nShaolin monk Liu Kang and his comrades, movie star Johnny Cage and military officer Sonya Blade were handpicked by Raiden, the god of thunder and defender of the Earth realm, to overcome their powerful adversaries in order to prevent Outworld from winning their tenth straight Mortal Kombat tournament. Each of the three has his or her own reason for competing: Liu seeks revenge against the tournament host Shang Tsung for killing his brother Chan; Sonya seeks revenge on an Australian crime lord Kano; and Cage, having been branded as a fake by the media, seeks to prove otherwise.\nAt Shang Tsung's island, Liu is attracted to Princess Kitana, Shao Kahn's adopted daughter. Aware that Kitana is a dangerous adversary because she is the rightful heir to Outworld and that she will attempt to ally herself with the Earth warriors, Tsung orders the creature Reptile to spy on her. Liu defeats his first opponent and Sonya gets her revenge on Kano by snapping his neck. Cage encounters and barely beats Scorpion. Liu engages in a brief duel with Kitana, who secretly offers him cryptic advice for his next battle. Liu's next opponent is Sub-Zero, whose defense seems untouched because of his freezing abilities, until Liu recalls Kitana's advice and uses it to kill Sub-Zero.\nPrince Goro enters the tournament and mercilessly crushes every opponent he faces. One of Cage's peers, Art Lean, is defeated by Goro as well and has his soul taken by Shang Tsung. Sonya worries that they may not win against Goro, but Raiden disagrees. He reveals their own fears and egos are preventing them from winning the tournament.\nDespite Sonya's warning, Cage comes to Tsung to request a fight with Goro. The sorcerer accepts on the condition that he be allowed to challenge any opponent of his choosing, anytime and anywhere he chooses. Raiden tries to intervene, but the conditions are agreed upon before he can do so. After Shang Tsung leaves, Raiden confronts Cage for what he has done in challenging Goro, but is impressed when Cage shows his awareness of the gravity of the tournament. Cage faces Goro and uses guile and the element of surprise to defeat the defending champion. Now desperate, Tsung takes Sonya hostage and takes her to Outworld, intending to fight her as his opponent. Knowing that his powers are ineffective there and that Sonya cannot defeat Tsung by herself, Raiden sends Liu and Cage into Outworld in order to rescue Sonya and challenge Tsung. In Outworld, Liu is attacked by Reptile, but eventually gains the upper hand and defeats him. Afterward, Kitana meets up with Cage and Liu, revealing to the pair the origins of both herself and Outworld. Kitana allies with them and helps them to infiltrate Tsung's castle.\nInside the castle tower, Shang Tsung challenges Sonya to fight him, claiming that her refusal to accept will result in the Earth realm forfeiting Mortal Kombat (this is, in fact, a lie on Shang's part). All seems lost for Earth realm until Kitana, Liu, and Cage appear. Kitana berates Tsung for his treachery to the Emperor as Sonya is set free. Tsung challenges Cage, but is counter-challenged by Liu. During the lengthy battle, Liu faces not only Tsung, but the souls that Tsung had forcibly taken in past tournaments. In a last-ditch attempt to take advantage, Tsung morphs into Chan. Seeing through the charade, Liu renews his determination and ultimately fires an energy bolt at the sorcerer, knocking him down and impaling him on a row of spikes. Tsung's death releases all of the captive souls, including Chan's. Before ascending to the afterlife, Chan tells Liu that he will remain with him in spirit until they are once again reunited, after Liu dies.\nThe warriors return to Earth realm, where a victory celebration is taking place at the Shaolin temple. The jubilation abruptly stops, however, when Shao Kahn's giant figure suddenly appears in the skies. When the Emperor declares that he has come for everyone's souls, the warriors take up fighting stances.", "title": "Mortal Kombat", "question_id": "40c1866a-b214-11ba-be57-8979d2cefa90", "question": "Where is Sonya taken to?", "answers": ["Outworld"], "no_answer": false }, "truncated_cells": [] }, { "row_idx": 151, "row": { "plot_id": "/m/03wj_q", "plot": "The film is centered on Mortal Kombat, a fighting tournament between the representatives of the realms of Earth and Outworld conceived by the Elder Gods amid looming invasion of the Earth by Outworld. If the realm of Outworld wins Mortal Kombat ten consecutive times, its Emperor Shao Kahn will be able to invade and conquer the Earth realm.\nShaolin monk Liu Kang and his comrades, movie star Johnny Cage and military officer Sonya Blade were handpicked by Raiden, the god of thunder and defender of the Earth realm, to overcome their powerful adversaries in order to prevent Outworld from winning their tenth straight Mortal Kombat tournament. Each of the three has his or her own reason for competing: Liu seeks revenge against the tournament host Shang Tsung for killing his brother Chan; Sonya seeks revenge on an Australian crime lord Kano; and Cage, having been branded as a fake by the media, seeks to prove otherwise.\nAt Shang Tsung's island, Liu is attracted to Princess Kitana, Shao Kahn's adopted daughter. Aware that Kitana is a dangerous adversary because she is the rightful heir to Outworld and that she will attempt to ally herself with the Earth warriors, Tsung orders the creature Reptile to spy on her. Liu defeats his first opponent and Sonya gets her revenge on Kano by snapping his neck. Cage encounters and barely beats Scorpion. Liu engages in a brief duel with Kitana, who secretly offers him cryptic advice for his next battle. Liu's next opponent is Sub-Zero, whose defense seems untouched because of his freezing abilities, until Liu recalls Kitana's advice and uses it to kill Sub-Zero.\nPrince Goro enters the tournament and mercilessly crushes every opponent he faces. One of Cage's peers, Art Lean, is defeated by Goro as well and has his soul taken by Shang Tsung. Sonya worries that they may not win against Goro, but Raiden disagrees. He reveals their own fears and egos are preventing them from winning the tournament.\nDespite Sonya's warning, Cage comes to Tsung to request a fight with Goro. The sorcerer accepts on the condition that he be allowed to challenge any opponent of his choosing, anytime and anywhere he chooses. Raiden tries to intervene, but the conditions are agreed upon before he can do so. After Shang Tsung leaves, Raiden confronts Cage for what he has done in challenging Goro, but is impressed when Cage shows his awareness of the gravity of the tournament. Cage faces Goro and uses guile and the element of surprise to defeat the defending champion. Now desperate, Tsung takes Sonya hostage and takes her to Outworld, intending to fight her as his opponent. Knowing that his powers are ineffective there and that Sonya cannot defeat Tsung by herself, Raiden sends Liu and Cage into Outworld in order to rescue Sonya and challenge Tsung. In Outworld, Liu is attacked by Reptile, but eventually gains the upper hand and defeats him. Afterward, Kitana meets up with Cage and Liu, revealing to the pair the origins of both herself and Outworld. Kitana allies with them and helps them to infiltrate Tsung's castle.\nInside the castle tower, Shang Tsung challenges Sonya to fight him, claiming that her refusal to accept will result in the Earth realm forfeiting Mortal Kombat (this is, in fact, a lie on Shang's part). All seems lost for Earth realm until Kitana, Liu, and Cage appear. Kitana berates Tsung for his treachery to the Emperor as Sonya is set free. Tsung challenges Cage, but is counter-challenged by Liu. During the lengthy battle, Liu faces not only Tsung, but the souls that Tsung had forcibly taken in past tournaments. In a last-ditch attempt to take advantage, Tsung morphs into Chan. Seeing through the charade, Liu renews his determination and ultimately fires an energy bolt at the sorcerer, knocking him down and impaling him on a row of spikes. Tsung's death releases all of the captive souls, including Chan's. Before ascending to the afterlife, Chan tells Liu that he will remain with him in spirit until they are once again reunited, after Liu dies.\nThe warriors return to Earth realm, where a victory celebration is taking place at the Shaolin temple. The jubilation abruptly stops, however, when Shao Kahn's giant figure suddenly appears in the skies. When the Emperor declares that he has come for everyone's souls, the warriors take up fighting stances.", "title": "Mortal Kombat", "question_id": "f1fdefcf-1191-b5f9-4cae-4ce4d0a59da7", "question": "Who took Goro's soul?", "answers": ["Shang Tsung."], "no_answer": false }, "truncated_cells": [] } ], "num_rows_total":60721, "num_rows_per_page":100, "partial":false }

Metrics

[More Information Needed] // https://datasets-server.huggingface.co/rows?dataset=uoft-cs/cifar100&config=cifar100&split=train&offset=0&length=1 { "features": [ { "feature_idx": 0, "name": "img", "type": { "type": "Image" } }, ... ], "rows": [ { "row_idx": 0, "row": { "img": { "src": "https://datasets-server.huggingface.co/cached-assets/uoft-cs/cifar100/--/aadb3af77e9048adbea6b47c21a81e47dd092ae5/--/cifar100/train/0/img/image.jpg?Expires=1710283469&Signature=A1v0cG07nuaBxYbuPR5EUZpJ9Se072SBDr4935gEsOESHGVyeqvd3qmvdsy1fuqbHk0dnx~p6MLtQ-hg3aCBOJ8eIJ5ItIoyYT4riJRuPQC0VFUb~b1maEwU8LRoXXuvrSysSz2QhBbC~ofv6cQudm~~bgGxXWAslDs180KnmPDsMU55ySsKyKQYNEkQKyuYvrGIJbFeg4lEps0f5CEwUstAwRAwlk~mzRpzUDBq7nJ~DcujTlllLv36nJX~too8mMnFn6dCn2nfGOFYwUiyYM73Czv-laLhVaIVUzcuJum90No~KNGzfYeFZpPqktA7MjCzRLf1gz5kA7wBqnY-8Q_&Key-Pair-Id=K3EI6M078Z3AC3", "height": 32, "width": 32 }, "fine_label": 19, "coarse_label": 11 }, "truncated_cells": [] } ], "num_rows_total":50000, "num_rows_per_page":100, "partial":false }

Results

[More Information Needed] import requests headers = {"Authorization": f"Bearer {API_TOKEN}"} API_URL = "https://datasets-server.huggingface.co/search?dataset=ibm/duorc&config=SelfRC&split=train&query=dog&offset=150&length=2" def query(): response = requests.get(API_URL, headers=headers) return response.json() data = query()

Summary

image/png

Model Examination [optional]

[More Information Needed] { "features": [ { "feature_idx": 0, "name": "plot_id", "type": { "dtype": "string", "_type": "Value" } }, { "feature_idx": 1, "name": "plot", "type": { "dtype": "string", "_type": "Value" } }, { "feature_idx": 2, "name": "title", "type": { "dtype": "string", "_type": "Value" } }, { "feature_idx": 3, "name": "question_id", "type": { "dtype": "string", "_type": "Value" } }, { "feature_idx": 4, "name": "question", "type": { "dtype": "string", "_type": "Value" } }, { "feature_idx": 5, "name": "answers", "type": { "feature": { "dtype": "string", "_type": "Value" }, "_type": "Sequence" } }, { "feature_idx": 6, "name": "no_answer", "type": { "dtype": "bool", "_type": "Value" } } ], "rows": [ { "row_idx": 1561, "row": { "plot_id": "/m/014bjk", "plot": "The film begins with clips that track a telephone call between London and Geneva, where a university student and part-time model, Valentine Dussault (Irène Jacob), is talking to her emotionally infantile and possessive boyfriend. During her work as a model she poses for a chewing-gum campaign and during the photo shoot the photographer asks her to look very sad. While walking back home, Auguste, a neighbour of Valentine's, drops a set of books, notices that a particular chapter of the Criminal Code opened at random, and concentrates on that passage. As she drives back to her apartment, Valentine is distracted while adjusting the radio and accidentally hits a dog. She tracks down the owner, a reclusive retired judge, Joseph Kern (Jean-Louis Trintignant). He seems unconcerned by the accident or the injuries sustained by Rita, his dog. Valentine takes Rita to a veterinarian, where she learns that Rita is pregnant. Valentine takes the dog home. Later, money is delivered to her apartment from an unnamed sender.\nWhilst Valentine is walking Rita the next day the dog runs away and Valentine eventually finds her back at Kern's house. She asks and he confirms that the money sent to her came from him, for the vet bill. He then tells Valentine she can have the dog. A short time later Valentine finds Kern eavesdropping on his neighbours' private telephone conversations. The judge challenges Valentine to go tell the neighbours and initially she goes to do so. She visits the neighbours' house, which appears, on the surface, to contain a contented nuclear family, causing her to change her mind about exposing their secrets. She returns to Kern's house and Kern tells her that it would make no difference if she denounced him for his spying because the people's lives he listens to would eventually turn into hell anyway. She leaves saying that she feels nothing but pity for him.\nWhilst visiting Kern, Valentine hears a phone conversation between her (unbeknownst to her) neighbour, Auguste, and his girlfriend, Karin (Frederique Feder). They discuss if they should go bowling. Valentine covers her ears but from the very little she hears she concludes that they love each other. Kern disagrees. That evening Valentine is alone at home and hopes that her boyfriend will call, but it is the photographer who calls, saying that her billboard was set up that evening and asks her to join them bowling to celebrate. Later, Auguste takes his exam and passes it and becomes a judge. Karin asks if he was asked any questions regarding the article that was open when he dropped his books. Auguste says yes. Karin gives him a fancy fountain pen as a gift and he wonders what the first judgment he signs with it will be. That evening, Kern writes a series of letters to his neighbours and the court confessing his activities, and the community files a class action. Later, at the law courts, he sees Karin make the acquaintance of and begin to flirt with another man. Earlier, Auguste had missed a call from Karin and tried to call her back but got no answer.\nValentine reads the news about a retired judge who spied on his neighbours and rushes to Kern's house to tell him that she did not report on him. He confesses that he turned himself in, just to see what she would do. He asks her in and shows her that Rita has had seven puppies. He tells her that in their last conversation when she spoke about pity he later realized that she really meant disgust. He ponders about the reasons why people obey laws and concludes that often it is more on selfish grounds and from fear than about obeying the law or being decent. It is his birthday and he offers her pear brandy for a toast. During their conversation he reminisces about a sailor he acquitted a long time ago, only later realizing he had made a mistake, and that the man was guilty. However, the man later married, had children and grandchildren and lives peacefully and happy. Valentine says that he did what he had to do, but Kern wonders how many other people that he acquitted or condemned might have seen a different life had he decided otherwise. Valentine tells Kern about her intended trip to England for a modeling job and to visit her boyfriend. Kern suggests that she take the ferry.\nAuguste has been unable to reach Karin since graduation so he goes to her place and sees her having sex with another man. Distraught, he leaves. Later, Auguste sees Karin and her new boyfriend in a restaurant. He gets her attention by tapping on the restaurant window with the pen she gave him. But when she rushes outside, he hides from her. In a temper, he ties his dog by a quayside and abandons him.\nKarin runs a service providing personalised weather information to travelers by telephone. Kern calls and enquires about the weather in the English Channel for the time when Valentine will be traveling to England. Karin states that she expects the weather to be perfect and reveals that she is about to take a trip there (with her new boyfriend who owns a yacht).\nThe day before Valentine leaves, she invites Kern to a fashion show where she is modeling. After the show they speak about the dream Kern had about her, where he saw her at the age of 50 and happy with an unidentified man. The conversation then turns to Kern and the reasons why he disliked Karin. Kern reveals that before becoming a judge, he was in love with a woman very much like Karin, who betrayed him for another man. While preparing for his exam, he once went to the same theatre where the fashion show took place and he accidentally dropped one of his books. When he picked it up, Kern studied the chapter where the book accidentally opened, which turned out to be the crucial question at his examination. After his girlfriend left him, he followed her across the English Channel but never saw her again, because she died in an accident. Later, he was assigned to judge a case where the defendant was the same man who took his girlfriend from him. Despite this connection, Kern did not recuse himself from the case and found the man guilty. He tells Valentine the judgment was entirely legal but also that he subsequently requested early retirement.\nValentine boards the ferry to England. Auguste is also on the ferry, clutching the dog he had temporarily abandoned. Although living in the same neighborhood and nearly crossing paths many times, the two have still never met. Suddenly a storm rises and sinks both the ferry and the boat with Karin and her boyfriend. Only seven survivors are pulled from the ferry: the main characters from the first two films of the trilogy, Julie and Olivier from Blue, Karol and Dominique from White, and Valentine and Auguste, who meet for the first time, as well as an English bartender named Stephen Killian. As in the previous films, the film's final sequence shows a character crying - in this case, the judge - but the final image replicates the iconic chewing-gum poster of Valentine, but this time with real emotion showing on her face.", "title": "Three Colors: Red", "question_id": "7c583513-0b7f-ddb3-be43-64befc7e90cc", "question": "Where is Valentine going on her trip?", "answers": ["England."], "no_answer": false }, "truncated_cells": [] }, { "row_idx": 1562, "row": { "plot_id": "/m/014bjk", "plot": "The film begins with clips that track a telephone call between London and Geneva, where a university student and part-time model, Valentine Dussault (Irène Jacob), is talking to her emotionally infantile and possessive boyfriend. During her work as a model she poses for a chewing-gum campaign and during the photo shoot the photographer asks her to look very sad. While walking back home, Auguste, a neighbour of Valentine's, drops a set of books, notices that a particular chapter of the Criminal Code opened at random, and concentrates on that passage. As she drives back to her apartment, Valentine is distracted while adjusting the radio and accidentally hits a dog. She tracks down the owner, a reclusive retired judge, Joseph Kern (Jean-Louis Trintignant). He seems unconcerned by the accident or the injuries sustained by Rita, his dog. Valentine takes Rita to a veterinarian, where she learns that Rita is pregnant. Valentine takes the dog home. Later, money is delivered to her apartment from an unnamed sender.\nWhilst Valentine is walking Rita the next day the dog runs away and Valentine eventually finds her back at Kern's house. She asks and he confirms that the money sent to her came from him, for the vet bill. He then tells Valentine she can have the dog. A short time later Valentine finds Kern eavesdropping on his neighbours' private telephone conversations. The judge challenges Valentine to go tell the neighbours and initially she goes to do so. She visits the neighbours' house, which appears, on the surface, to contain a contented nuclear family, causing her to change her mind about exposing their secrets. She returns to Kern's house and Kern tells her that it would make no difference if she denounced him for his spying because the people's lives he listens to would eventually turn into hell anyway. She leaves saying that she feels nothing but pity for him.\nWhilst visiting Kern, Valentine hears a phone conversation between her (unbeknownst to her) neighbour, Auguste, and his girlfriend, Karin (Frederique Feder). They discuss if they should go bowling. Valentine covers her ears but from the very little she hears she concludes that they love each other. Kern disagrees. That evening Valentine is alone at home and hopes that her boyfriend will call, but it is the photographer who calls, saying that her billboard was set up that evening and asks her to join them bowling to celebrate. Later, Auguste takes his exam and passes it and becomes a judge. Karin asks if he was asked any questions regarding the article that was open when he dropped his books. Auguste says yes. Karin gives him a fancy fountain pen as a gift and he wonders what the first judgment he signs with it will be. That evening, Kern writes a series of letters to his neighbours and the court confessing his activities, and the community files a class action. Later, at the law courts, he sees Karin make the acquaintance of and begin to flirt with another man. Earlier, Auguste had missed a call from Karin and tried to call her back but got no answer.\nValentine reads the news about a retired judge who spied on his neighbours and rushes to Kern's house to tell him that she did not report on him. He confesses that he turned himself in, just to see what she would do. He asks her in and shows her that Rita has had seven puppies. He tells her that in their last conversation when she spoke about pity he later realized that she really meant disgust. He ponders about the reasons why people obey laws and concludes that often it is more on selfish grounds and from fear than about obeying the law or being decent. It is his birthday and he offers her pear brandy for a toast. During their conversation he reminisces about a sailor he acquitted a long time ago, only later realizing he had made a mistake, and that the man was guilty. However, the man later married, had children and grandchildren and lives peacefully and happy. Valentine says that he did what he had to do, but Kern wonders how many other people that he acquitted or condemned might have seen a different life had he decided otherwise. Valentine tells Kern about her intended trip to England for a modeling job and to visit her boyfriend. Kern suggests that she take the ferry.\nAuguste has been unable to reach Karin since graduation so he goes to her place and sees her having sex with another man. Distraught, he leaves. Later, Auguste sees Karin and her new boyfriend in a restaurant. He gets her attention by tapping on the restaurant window with the pen she gave him. But when she rushes outside, he hides from her. In a temper, he ties his dog by a quayside and abandons him.\nKarin runs a service providing personalised weather information to travelers by telephone. Kern calls and enquires about the weather in the English Channel for the time when Valentine will be traveling to England. Karin states that she expects the weather to be perfect and reveals that she is about to take a trip there (with her new boyfriend who owns a yacht).\nThe day before Valentine leaves, she invites Kern to a fashion show where she is modeling. After the show they speak about the dream Kern had about her, where he saw her at the age of 50 and happy with an unidentified man. The conversation then turns to Kern and the reasons why he disliked Karin. Kern reveals that before becoming a judge, he was in love with a woman very much like Karin, who betrayed him for another man. While preparing for his exam, he once went to the same theatre where the fashion show took place and he accidentally dropped one of his books. When he picked it up, Kern studied the chapter where the book accidentally opened, which turned out to be the crucial question at his examination. After his girlfriend left him, he followed her across the English Channel but never saw her again, because she died in an accident. Later, he was assigned to judge a case where the defendant was the same man who took his girlfriend from him. Despite this connection, Kern did not recuse himself from the case and found the man guilty. He tells Valentine the judgment was entirely legal but also that he subsequently requested early retirement.\nValentine boards the ferry to England. Auguste is also on the ferry, clutching the dog he had temporarily abandoned. Although living in the same neighborhood and nearly crossing paths many times, the two have still never met. Suddenly a storm rises and sinks both the ferry and the boat with Karin and her boyfriend. Only seven survivors are pulled from the ferry: the main characters from the first two films of the trilogy, Julie and Olivier from Blue, Karol and Dominique from White, and Valentine and Auguste, who meet for the first time, as well as an English bartender named Stephen Killian. As in the previous films, the film's final sequence shows a character crying - in this case, the judge - but the final image replicates the iconic chewing-gum poster of Valentine, but this time with real emotion showing on her face.", "title": "Three Colors: Red", "question_id": "80becb22-908d-84bc-3a5f-00b620d551bc", "question": "What was the profession of the dog's owner?", "answers": ["Retired Judge"], "no_answer": false }, "truncated_cells": [] } ], "num_rows_total": 5247, "num_rows_per_page": 100, "partial": false }

Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

  • Hardware Type: [More Information Needed] { "features":[ { "feature_idx":0, "name":"plot_id", "type":{ "dtype":"string", "_type":"Value" } }, { "feature_idx":1, "name":"plot", "type":{ "dtype":"string", "_type":"Value" } }, { "feature_idx":2, "name":"title", "type":{ "dtype":"string", "_type":"Value" } }, { "feature_idx":3, "name":"question_id", "type":{ "dtype":"string", "_type":"Value" } }, { "feature_idx":4, "name":"question", "type":{ "dtype":"string", "_type":"Value" } }, { "feature_idx":5, "name":"answers", "type":{ "feature":{ "dtype":"string", "_type":"Value" }, "_type":"Sequence" } }, { "feature_idx":6, "name":"no_answer", "type":{ "dtype":"bool", "_type":"Value" } } ], "rows":[ { "row_idx":12825, "row":{ "plot_id":"/m/06qxsf", "plot":"Prologue\nA creepy-looking coroner introduces three different horror tales involving his current work on cadavers in "body bags".\n"The Gas Station"[edit]\nAnne is a young college student who arrives for her first job working the night shift at an all-night filling station near Haddonfield, Illinois (a reference to the setting of Carpenter's two Halloween films). The attending worker, Bill, tells her that a serial killer has broken out of a mental hospital, and cautions her not to leave the booth at the station without the keys because the door locks automatically. After Bill leaves, Anne is alone and the tension mounts as she deals with various late-night customers seeking to buy gas for a quick fill-up, purchase cigarettes or just use the restroom key, unsure whether any of them might be the escaped maniac. Eventually, when Anne suspects that the escaped killer is lurking around the gas station, she tries to call the police, only to find that the phone line is dead. Soon after that, she finds an elaborately grotesque drawing in the Restroom and then the dead body of a transient sitting in a pickup truck on the lift in one of the garage bays. She makes a phone call for help which results in her realization that "Bill", the attending worker she met earlier, is in fact the escaped killer, who has killed the real Bill and is killing numerous passers-by. She finds the real Bill's dead body in one of the lockers. Serial Killer "Bill" then reappears and attempts to kill Anne with a machete, breaking into the locked booth by smashing out the glass with a sledgehammer and then chasing her around the deserted garage. Just as he is about to kill her, a customer returns, having forgotten his credit card, and he wrestles the killer, giving Anne time to crush him under the vehicle lift.\n"Hair"[edit]\nRichard Coberts is a middle-aged businessman who is very self-conscious about his thinning hair. This obsession has caused a rift between him and his long-suffering girlfriend Megan. Richard answers a television ad about a "miracle" hair transplant operation, pays a visit to the office, and meets the shady Dr. Lock, who, for a very large fee, agrees to give Richard a surgical procedure to make his hair grow back. The next day, Richard wakes up and removes the bandage around his head, and is overjoyed to find that he has a full head of hair. But soon he becomes increasingly sick and fatigued, and finds his hair continuing to grow and, additionally, growing out of parts of his body, where hair does not normally grow. Trying to cut some of the hair off, he finds that it "bleeds", and, examining some of the hairs under a magnifying glass, sees that they are alive and resemble tiny serpents. He goes back to Dr. Lock for an explanation, but finds himself a prisoner as Dr. Lock explains that he and his entire staff are aliens from another planet, seeking out narcissistic human beings and planting seeds of "hair" to take over their bodies for consumption as part of their plan to spread their essence to Earth.\n"Eye"[edit]\nBrent Matthews is a baseball player whose life and career take a turn for the worse when he gets into a serious car accident in which his right eye is gouged out. Unwilling to admit that his career is over, he jumps at the chance to undergo an experimental surgical procedure to replace his eye with one from a recently deceased person. But soon after the surgery he begins to see things out of his new eye that others cannot see, and begins having nightmares of killing women and having sex with them. Brent seeks out the doctor who operated on him, and the doctor tells him that the donor of his new eye was a recently executed serial killer and necrophile who killed several young women, and then had sex with their dead bodies. Brent becomes convinced that the spirit of the dead killer is taking over his body so that he can resume killing women. He flees back to his house and tells his skeptical wife, Cathy, about what is happening. Just then the spirit of the killer emerges and attempts to kill Cathy as well. Cathy fights back, subduing him long enough for Brent to re-emerge. Realizing that it is only a matter of time before the killer emerges again, Brent cuts out his donated eye, severing his link with the killer, but then bleeds to death.\nEpilogue The coroner is finishing telling his last tale when he hears a noise from outside the morgue. He crawls back inside a body bag, revealing that he himself is a living cadaver, as two other morgue workers begin to go to work on his "John Doe" corpse.", "title":"John Carpenter presents Body Bags", "question_id":"cf58489f-12ba-ace6-67a7-010d957b4ff4", "question":"What happens soon after the surgery?", "answers":[
    ], "no_answer":true }, "truncated_cells":[
    ] }, { "row_idx":12836, "row":{ "plot_id":"/m/04z_3pm", "plot":"In 1976, eight-year-old Mary Daisy Dinkle (Bethany Whitmore) lives a lonely life in Mount Waverley, Australia. At school, she is teased by her classmates because of an unfortunate birthmark on her forehead; while at home, her distant father, Noel, and alcoholic, kleptomaniac mother, Vera, provide little support. Her only comforts are her pet rooster, Ethel; her favourite food, sweetened condensed milk; and a Smurfs-like cartoon show called The Noblets. One day, while at the post office with her mother, Mary spots a New York City telephone book and, becoming curious about Americans, decides to write to one. She randomly chooses Max Jerry Horowitz's name from the phone book and writes him a letter telling him about herself, sending it off in the hope that he will become her pen friend.\nMax Jerry Horowitz (Philip Seymour Hoffman) is a morbidly obese 44-year-old ex-Jewish atheist who has trouble forming close bonds with other people, due to various mental and social problems. Though Mary's letter initially gives him an anxiety attack, he decides to write back to her, and the two quickly become friends (partly due to their shared love of chocolate and The Noblets). Due to Vera's disapproval of Max, Mary tells him to send his letters to her agoraphobic neighbour, Len Hislop, whose mail she collects regularly. When Mary later asks Max about love, he suffers a severe anxiety attack and is institutionalized for eight months. After his release, he is hesitant to write to Mary again for some time. On his 48th birthday, he wins the New York lottery, using his winnings to buy a lifetime supply of chocolate and an entire collection of Noblet figurines. He gives the rest of his money to his elderly neighbour Ivy, who uses most of it to pamper herself before dying in an accident with a malfunctioning jet pack. Meanwhile, Mary becomes despondent, thinking Max has abandoned her.\nOn the advice of his therapist, Max finally writes back to Mary and explains he has been diagnosed with Asperger syndrome. Mary is thrilled to hear from him again, and the two continue their correspondence for the next several years. When Noel retires from his job at a tea bag factory, he takes up metal detecting, but is soon swept away (and presumably killed) by a big tidal bore while on a beach. Mary (Toni Colette) goes to university and has her birthmark surgically removed, and develops a crush on her Greek Australian neighbour, Damien Popodopoulos (Eric Bana). Drunk and guilt-ridden over her husband's death, Vera accidentally kills herself after she drinks embalming fluid (which she mistook for cooking sherry). Mary and Damien grow closer following Vera's death and are later married.\nInspired by her friendship with Max, Mary studies psychology at university, writing her doctoral dissertation on Asperger syndrome with Max as her test subject. She plans to have her dissertation published as a book; but when Max receives a copy from her, he is infuriated that she has taken advantage of his condition, which he sees as an integral part of his personality and not a disability that needs to be cured. He breaks off communication with Mary (by removing the letter "M" from his typewriter), who, heartbroken, has the entire run of her book pulped, effectively ending her budding career. She sinks into depression and begins drinking cooking sherry, as her mother had done. While searching through a cabinet, she finds a can of condensed milk, and sends it to Max as an apology. She checks the post daily for a response and one day finds a note from Damien, informing her that he has left her for his own pen friend, Desmond, a sheep farmer in New Zealand.\nMeanwhile, after an incident in which he nearly chokes a homeless man (Ian "Molly" Meldrum) in anger, after throwing a used cigarette, Max realizes Mary is an imperfect human being, like himself, and sends her a package containing his Noblet figurine collection as a sign of forgiveness. Mary, however, has sunken into despair after Damien's departure, and fails to find the package on her doorstep for several days. Finding some Valium that had belonged to her mother, and unaware that she is pregnant with Damien's child, Mary decides to commit suicide. As she takes the Valium and is on the verge of hanging herself, Len knocks on her door, having conquered his agoraphobia to alert her of Max's package. Inside, she finds the Noblet figurines and a letter from Max, in which he tells her of his realization that they are not perfect and expresses his forgiveness. He also states how much their friendship means to him, and that he hopes their paths will cross one day.\nOne year later, Mary travels to New York with her infant child to finally visit Max. Entering his apartment, Mary discovers Max on his couch, gazing upward with a smile on his face, having died earlier that morning. Looking around the apartment, Mary is awestruck to find all the letters she had sent to Max over the years, laminated and taped to the ceiling. Realizing Max had been gazing at the letters when he died, and seeing how much he had valued their friendship, Mary cries tears of joy and joins him on the couch.", "title":"Mary and Max", "question_id":"1dc019ad-80cf-1d49-5a69-368f90fae2f8", "question":"Why was Mary Daisy Dinkle teased in school?", "answers":[
    ], "no_answer":true }, "truncated_cells":[
    ] } ], "num_rows_total":627, "num_rows_per_page":100, "partial":false

}

}

}

}

Technical Specifications [optional]

bombastictranz/romeo-rosete

Model Architecture and Objective

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Compute Infrastructure

[More Information Needed] { "@context": { "@language": "en", "@vocab": "https://schema.org/", "citeAs": "cr:citeAs", "column": "cr:column", "conformsTo": "dct:conformsTo", "cr": "http://mlcommons.org/croissant/", "data": { "@id": "cr:data", "@type": "@json" }, "dataBiases": "cr:dataBiases", "dataCollection": "cr:dataCollection", "dataType": { "@id": "cr:dataType", "@type": "@vocab" }, "dct": "http://purl.org/dc/terms/", "extract": "cr:extract", "field": "cr:field", "fileProperty": "cr:fileProperty", "fileObject": "cr:fileObject", "fileSet": "cr:fileSet", "format": "cr:format", "includes": "cr:includes", "isLiveDataset": "cr:isLiveDataset", "jsonPath": "cr:jsonPath", "key": "cr:key", "md5": "cr:md5", "parentField": "cr:parentField", "path": "cr:path", "personalSensitiveInformation": "cr:personalSensitiveInformation", "recordSet": "cr:recordSet", "references": "cr:references", "regex": "cr:regex", "repeated": "cr:repeated", "replace": "cr:replace", "sc": "https://schema.org/", "separator": "cr:separator", "source": "cr:source", "subField": "cr:subField", "transform": "cr:transform" }, "@type": "sc:Dataset", "distribution": [ { "@type": "cr:FileObject", "@id": "repo", "name": "repo", "description": "The Hugging Face git repository.", "contentUrl": "https://huggingface.co/datasets/ibm/duorc/tree/refs%2Fconvert%2Fparquet", "encodingFormat": "git+https", "sha256": "https://github.com/mlcommons/croissant/issues/80" }, { "@type": "cr:FileSet", "@id": "parquet-files-for-config-ParaphraseRC", "name": "parquet-files-for-config-ParaphraseRC", "description": "The underlying Parquet files as converted by Hugging Face (see: https://huggingface.co/docs/dataset-viewer/parquet).", "containedIn": { "@id": "repo" }, "encodingFormat": "application/x-parquet", "includes": "ParaphraseRC//.parquet" }, { "@type": "cr:FileSet", "@id": "parquet-files-for-config-SelfRC", "name": "parquet-files-for-config-SelfRC", "description": "The underlying Parquet files as converted by Hugging Face (see: https://huggingface.co/docs/dataset-viewer/parquet).", "containedIn": { "@id": "repo" }, "encodingFormat": "application/x-parquet", "includes": "SelfRC//.parquet" } ], "recordSet": [ { "@type": "cr:RecordSet", "@id": "ParaphraseRC", "name": "ParaphraseRC", "description": "ibm/duorc - 'ParaphraseRC' subset\n\nAdditional information:\n- 3 splits: train, validation, test\n- 1 skipped column: answers", "field": [ { "@type": "cr:Field", "@id": "ParaphraseRC/plot_id", "name": "ParaphraseRC/plot_id", "description": "Column 'plot_id' from the Hugging Face parquet file.", "dataType": "sc:Text", "source": { "fileSet": { "@id": "parquet-files-for-config-ParaphraseRC" }, "extract": { "column": "plot_id" } } }, { "@type": "cr:Field", "@id": "ParaphraseRC/plot", "name": "ParaphraseRC/plot", "description": "Column 'plot' from the Hugging Face parquet file.", "dataType": "sc:Text", "source": { "fileSet": { "@id": "parquet-files-for-config-ParaphraseRC" }, "extract": { "column": "plot" } } }, { "@type": "cr:Field", "@id": "ParaphraseRC/title", "name": "ParaphraseRC/title", "description": "Column 'title' from the Hugging Face parquet file.", "dataType": "sc:Text", "source": { "fileSet": { "@id": "parquet-files-for-config-ParaphraseRC" }, "extract": { "column": "title" } } }, { "@type": "cr:Field", "@id": "ParaphraseRC/question_id", "name": "ParaphraseRC/question_id", "description": "Column 'question_id' from the Hugging Face parquet file.", "dataType": "sc:Text", "source": { "fileSet": { "@id": "parquet-files-for-config-ParaphraseRC" }, "extract": { "column": "question_id" } } }, { "@type": "cr:Field", "@id": "ParaphraseRC/question", "name": "ParaphraseRC/question", "description": "Column 'question' from the Hugging Face parquet file.", "dataType": "sc:Text", "source": { "fileSet": { "@id": "parquet-files-for-config-ParaphraseRC" }, "extract": { "column": "question" } } }, { "@type": "cr:Field", "@id": "ParaphraseRC/no_answer", "name": "ParaphraseRC/no_answer", "description": "Column 'no_answer' from the Hugging Face parquet file.", "dataType": "sc:Boolean", "source": { "fileSet": { "@id": "parquet-files-for-config-ParaphraseRC" }, "extract": { "column": "no_answer" } } } ] }, { "@type": "cr:RecordSet", "@id": "SelfRC", "name": "SelfRC", "description": "ibm/duorc - 'SelfRC' subset\n\nAdditional information:\n- 3 splits: train, validation, test\n- 1 skipped column: answers", "field": [ { "@type": "cr:Field", "@id": "SelfRC/plot_id", "name": "SelfRC/plot_id", "description": "Column 'plot_id' from the Hugging Face parquet file.", "dataType": "sc:Text", "source": { "fileSet": { "@id": "parquet-files-for-config-SelfRC" }, "extract": { "column": "plot_id" } } }, { "@type": "cr:Field", "@id": "SelfRC/plot", "name": "SelfRC/plot", "description": "Column 'plot' from the Hugging Face parquet file.", "dataType": "sc:Text", "source": { "fileSet": { "@id": "parquet-files-for-config-SelfRC" }, "extract": { "column": "plot" } } }, { "@type": "cr:Field", "@id": "SelfRC/title", "name": "SelfRC/title", "description": "Column 'title' from the Hugging Face parquet file.", "dataType": "sc:Text", "source": { "fileSet": { "@id": "parquet-files-for-config-SelfRC" }, "extract": { "column": "title" } } }, { "@type": "cr:Field", "@id": "SelfRC/question_id", "name": "SelfRC/question_id", "description": "Column 'question_id' from the Hugging Face parquet file.", "dataType": "sc:Text", "source": { "fileSet": { "@id": "parquet-files-for-config-SelfRC" }, "extract": { "column": "question_id" } } }, { "@type": "cr:Field", "@id": "SelfRC/question", "name": "SelfRC/question", "description": "Column 'question' from the Hugging Face parquet file.", "dataType": "sc:Text", "source": { "fileSet": { "@id": "parquet-files-for-config-SelfRC" }, "extract": { "column": "question" } } }, { "@type": "cr:Field", "@id": "SelfRC/no_answer", "name": "SelfRC/no_answer", "description": "Column 'no_answer' from the Hugging Face parquet file.", "dataType": "sc:Boolean", "source": { "fileSet": { "@id": "parquet-files-for-config-SelfRC" }, "extract": { "column": "no_answer" } } } ] } ], "name": "duorc", "description": "\n\t\n\t\t\n\t\n\t\n\t\tDataset Card for duorc\n\t\n\n\n\t\n\t\t\n\t\n\t\n\t\tDataset Summary\n\t\n\nThe DuoRC dataset is an English language dataset of questions and answers gathered from crowdsourced AMT workers on Wikipedia and IMDb movie plots. The workers were given freedom to pick answer from the plots or synthesize their own answers. It contains two sub-datasets - SelfRC and ParaphraseRC. SelfRC dataset is built on Wikipedia movie plots solely. ParaphraseRC has questions written from Wikipedia movie plots and the… See the full description on the dataset page: https://huggingface.co/datasets/ibm/duorc.", "alternateName": [ "ibm/duorc", "DuoRC" ], "creator": { "@type": "Organization", "name": "IBM", "url": "https://huggingface.co/ibm" }, "keywords": [ "question-answering", "text2text-generation", "abstractive-qa", "extractive-qa", "crowdsourced", "crowdsourced", "monolingual", "100K<n<1M", "10K<n<100K", "original", "English", "mit", "Croissant", "arxiv:1804.07927", "🇺🇸 Region: US" ], "license": "https://choosealicense.com/licenses/mit/", "sameAs": "https://duorc.github.io/", "url": "https://huggingface.co/datasets/ibm/duorc" }

Hardware

[More Information Needed] curl https://clickhouse.com/ | sh

Software

image/png

[More Information Needed] def encode(examples): return tokenizer(examples["sentence1"], examples["sentence2"], truncation=True, padding="max_length")

dataset = dataset.map(encode, batched=True) dataset[0] import requests

r = requests.get("https://datasets-server.huggingface.co/parquet?dataset=maharshipandya/spotify-tracks-dataset") j = r.json() url = [f['url'] for f in j['parquet_files']] url ['https://huggingface.co/datasets/maharshipandya/spotify-tracks-dataset/resolve/refs%2Fconvert%2Fparquet/default/train/0000.parquet']

Citation [optional]

BibTeX:

[More Information Needed] ./clickhouse local -q " SELECT count() AS c, artists FROM url('https://huggingface.co/datasets/maharshipandya/spotify-tracks-dataset/resolve/refs%2Fconvert%2Fparquet/default/train/0000.parquet') GROUP BY artists ORDER BY c DESC LIMIT 5 SETTINGS enable_url_encoding=0, max_http_get_redirects=1"

┌───c─┬─artists─────────┐ │ 279 │ The Beatles │ │ 271 │ George Jones │ │ 236 │ Stevie Wonder │ │ 224 │ Linkin Park │ │ 222 │ Ella Fitzgerald │ └─────┴─────────────────┘

APA:

[More Information Needed] ./clickhouse local -q " SELECT round(danceability, 1) AS danceability, bar(count(), 0, max(count()) OVER ()) AS dist FROM url('https://huggingface.co/datasets/maharshipandya/spotify-tracks-dataset/resolve/refs%2Fconvert%2Fparquet/default/train/0000.parquet') GROUP BY danceability ORDER BY danceability ASC SETTINGS enable_url_encoding=0, max_http_get_redirects=1"

┌─danceability─┬─dist─────────────────────────────────────────────────────────────────────────────────┐ │ 0 │ ▍ │ │ 0.1 │ ████▎ │ │ 0.2 │ █████████████▍ │ │ 0.3 │ ████████████████████████ │ │ 0.4 │ ████████████████████████████████████████████▋ │ │ 0.5 │ ████████████████████████████████████████████████████████████████████▊ │ │ 0.6 │ ████████████████████████████████████████████████████████████████████████████████ │ │ 0.7 │ ██████████████████████████████████████████████████████████████████████ │ │ 0.8 │ ██████████████████████████████████████████ │ │ 0.9 │ ██████████▋ │ │ 1 │ ▌ │ └──────────────┴──────────────────────────────────────────────────────────────────────────────────────┘

Glossary [optional]

[More Information Needed] ./clickhouse local

More Information [optional]

[More Information Needed] CREATE OR REPLACE FUNCTION hugging_paths AS dataset -> ( SELECT arrayMap(x -> (x.1), JSONExtract(json, 'parquet_files', 'Array(Tuple(url String))')) FROM url('https://datasets-server.huggingface.co/parquet?dataset=' || dataset, 'JSONAsString') );

SELECT hugging_paths('tasksource/blog_authorship_corpus') AS paths

['https://huggingface.co/datasets/tasksource/blog_authorship_corpus/resolve/refs%2Fconvert%2Fparquet/default/train/0000.parquet','https://huggingface.co/datasets/tasksource/blog_authorship_corpus/resolve/refs%2Fconvert%2Fparquet/default/train/0001.parquet']

Model Card Authors [optional]

[More Information Needed] CREATE OR REPLACE FUNCTION hf AS dataset -> ( WITH hugging_paths(dataset) as urls SELECT multiIf(length(urls) = 0, '', length(urls) = 1, urls[1], 'https://huggingface.co/datasets/{' || arrayStringConcat(arrayMap(x -> replaceRegexpOne(replaceOne(x, 'https://huggingface.co/datasets/', ''), '\.parquet$', ''), urls), ',') || '}.parquet') );

SELECT hf('tasksource/blog_authorship_corpus') AS pattern

https://huggingface.co/datasets/{tasksource/blog_authorship_corpus/resolve/refs%2Fconvert%2Fparquet/default/train/0000,tasksource/blog_authorship_corpus/resolve/refs%2Fconvert%2Fparquet/default/train/0001}.parquet

Model Card Contact

[More Information Needed] SELECT sign, count(*), AVG(LENGTH(text)) AS avg_blog_length FROM url(hf('tasksource/blog_authorship_corpus')) GROUP BY sign ORDER BY avg_blog_length DESC LIMIT(5)

┌───────────┬────────┬────────────────────┐ │ sign │ count │ avg_blog_length │ ├───────────┼────────┼────────────────────┤ │ Aquarius │ 49687 │ 1193.9523819107615 │ │ Leo │ 53811 │ 1186.0665291483153 │ │ Cancer │ 65048 │ 1160.8010392325666 │ │ Gemini │ 51985 │ 1158.4132922958545 │ │ Vurgi │ 60399 │ 1142.9977648636566 │ └───────────┴────────┴────────────────────┘

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