Llama 4
Collection
Llama 4 release
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10 items
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Updated
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439
Rajat Arya
rajatarya
AI & ML interests
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Recent Activity
new activity
10 days ago
meta-llama/Llama-4-Maverick-17B-128E-Instruct:[request for feedback] faster downloads with xet
new activity
15 days ago
meta-llama/Llama-4-Scout-17B-16E-Instruct:[request for feedback] Faster downloads with Xet
upvoted
a
collection
16 days ago
Llama 4
Organizations
rajatarya's activity
[request for feedback] faster downloads with xet
4
#18 opened 16 days ago
by
clem
[request for feedback] Faster downloads with Xet
12
18
#16 opened 16 days ago
by
clem
upvoted
a
collection
16 days ago
upvoted
an
article
16 days ago
Article
Welcome Llama 4 Maverick & Scout on Hugging Face!
By
and 6 others
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140
published
an
article
17 days ago
Article
Welcome Llama 4 Maverick & Scout on Hugging Face!
By
and 6 others
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140
published
a
model
24 days ago
Let's go! Get on the waitlist - can't wait to get you onboarded with Xet. From a customer onboarding last week, "Yeah, it's pretty seamless.... oh wait, that was fast."
reacted to
jsulz's
post with ❤️🚀
about 1 month ago
Post
1437
It's finally here ❤️
Build faster than ever with lightning fast upload and download speeds starting today on the Hub ⚡
Xet storage is rolling out access across the Hub - join the waitlist here https://huggingface.co/join/xet
You can apply for yourself, or your entire organization. Head over to your account settings for more information or join anywhere you see the Xet logo on a repository you know.
Have questions? Join the conversation below 👇 or open a discussion on the Xet team page xet-team/README
Build faster than ever with lightning fast upload and download speeds starting today on the Hub ⚡
Xet storage is rolling out access across the Hub - join the waitlist here https://huggingface.co/join/xet
You can apply for yourself, or your entire organization. Head over to your account settings for more information or join anywhere you see the Xet logo on a repository you know.
Have questions? Join the conversation below 👇 or open a discussion on the Xet team page xet-team/README
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- 6 replies
upvoted
an
article
2 months ago
Article
From Chunks to Blocks: Accelerating Uploads and Downloads on the Hub
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62
reacted to
jsulz's
post with 👀👍🔥
4 months ago
Post
1439
Doing a lot of benchmarking and visualization work, which means I'm always searching for interesting repos in terms of file types, size, branches, and overall structure.
To help, I built a Space jsulz/repo-info that lets you search for any repo and get back:
- Treemap of the repository, color coded by file/directory size
- Repo branches and their size
- Cumulative size of different file types (e.g., the total size of all the safetensors in the repo)
And because I'm interested in how this will fit in our work to leverage content-defined chunking for versioning repos on the Hub
- https://huggingface.co/blog/from-files-to-chunks - everything has the number of chunks (1 chunk = 64KB) as well as the total size in bytes.
Some of the treemaps are pretty cool. Attached are black-forest-labs/FLUX.1-dev and for fun laion/laion-audio-preview (which has nearly 10k .tar files 🤯)
To help, I built a Space jsulz/repo-info that lets you search for any repo and get back:
- Treemap of the repository, color coded by file/directory size
- Repo branches and their size
- Cumulative size of different file types (e.g., the total size of all the safetensors in the repo)
And because I'm interested in how this will fit in our work to leverage content-defined chunking for versioning repos on the Hub
- https://huggingface.co/blog/from-files-to-chunks - everything has the number of chunks (1 chunk = 64KB) as well as the total size in bytes.
Some of the treemaps are pretty cool. Attached are black-forest-labs/FLUX.1-dev and for fun laion/laion-audio-preview (which has nearly 10k .tar files 🤯)
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- 2 replies
replied to
cfahlgren1's
post
5 months ago
Also - easily reference your datasets in your research, giving conference committees greater confidence in the reproducibility of your results (ex. share the dataset, the model, the paper, and the analysis - all on the Hub).
Research needs reproducibility, use HF Hub for collaboration & dissemination:
- Data: Hub Dataset (https://huggingface.co/new-dataset)
- Model: Hub Model (https://huggingface.co/new)
- Paper: Hub Papers (https://huggingface.co/papers)
- Analysis / Results: Hub Spaces (https://huggingface.co/spaces)
upvoted
an
article
6 months ago
Article
Improving Parquet Dedupe on Hugging Face Hub
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33
upvoted
an
article
8 months ago
Article
The 5 Most Under-Rated Tools on Hugging Face
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87
upvoted
an
article
9 months ago
Article
XetHub is joining Hugging Face!
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92