datatab
/

Yugo55A-4bit

@@ -1,202 +1,192 @@
 ---
 library_name: transformers
 tags:
-- unsloth
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 ---
+base_model:
+- mlabonne/AlphaMonarch-7B
+- datatab/Yugo55-GPT-v4
+- datatab/Yugo55-GPT-DPO-v1-chkp-300
+- NousResearch/Nous-Hermes-2-Mistral-7B-DPO
 library_name: transformers
 tags:
+- mergekit
+- merge
+- text-generation-inference
+- transformers
+- mistral
+license: mit
+language:
+- sr
+datasets:
+- datatab/alpaca-cleaned-serbian-full
+- datatab/ultrafeedback_binarized
+- datatab/open-orca-slim-serbian
 ---
+# Yugo55A-GPT
+- **Developed by:** datatab
+- **License:** mit
+## 🏆 Results
+> Results obtained through the Serbian LLM evaluation, released by Aleksa Gordić: [serbian-llm-eval](https://github.com/gordicaleksa/serbian-llm-eval)
+> * Evaluation was conducted on a 4-bit version of the model due to hardware resource constraints.
+<table>
+  <tr>
+    <th>MODEL</th>
+    <th>ARC-E</th>
+    <th>ARC-C</th>
+    <th>Hellaswag</th>
+    <th>BoolQ</th>
+    <th>Winogrande</th>
+    <th>OpenbookQA</th>
+    <th>PiQA</th>
+  </tr>
+  <tr>
+    <td><a href="https://huggingface.co/datatab/Yugo55-GPT-v4-4bit/">*Yugo55-GPT-v4-4bit</a></td>
+    <td>51.41</td>
+    <td>36.00</td>
+    <td>57.51</td>
+    <td>80.92</td>
+    <td><strong>65.75</strong></td>
+    <td>34.70</td>
+    <td><strong>70.54</strong></td>
+  </tr>
+  <tr>
+    <td><a href="https://huggingface.co/datatab/Yugo55A-GPT/">Yugo55A-GPT</a></td>
+    <td><strong>51.52</strong></td>
+    <td><strong>37.78</strong></td>
+    <td><strong>57.52</strong></td>
+    <td><strong>84.40</strong></td>
+    <td>65.43</td>
+    <td><strong>35.60</strong></td>
+    <td>69.43</td>
+  </tr>
+</table>
+# 🔗 Merge Details
+### Merge Method
+> This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
+> This model was merged using the [linear](https://arxiv.org/abs/2203.05482) merge method.
+### Models Merged
+The following models were included in the merge:
+* [datatab/Yugo55-GPT-v4](https://huggingface.co/datatab/Yugo55-GPT-v4)
+* [datatab/Yugo55-GPT-DPO-v1-chkp-300](https://huggingface.co/datatab/Yugo55-GPT-DPO-v1-chkp-300)
+* [mlabonne/AlphaMonarch-7B](https://huggingface.co/mlabonne/AlphaMonarch-7B)
+* [NousResearch/Nous-Hermes-2-Mistral-7B-DPO](https://huggingface.co/NousResearch/Nous-Hermes-2-Mistral-7B-DPO)
+## 🧩 Configuration
+The following YAML configuration was used to produce this model:
+```yaml
+models:
+  - model: datatab/Yugo55-GPT-v4
+    parameters:
+      weight: 1.0
+  - model: datatab/Yugo55-GPT-DPO-v1-chkp-300
+    parameters:
+      weight: 1.0
+  - model: mlabonne/AlphaMonarch-7B
+    parameters:
+      weight: 0.5
+  - model: NousResearch/Nous-Hermes-2-Mistral-7B-DPO
+    parameters:
+      weight: 0.5
+merge_method: linear
+dtype: float16
+```
+## 💻 Usage
+```terminal
+!pip -q install git+https://github.com/huggingface/transformers # need to install from github
+!pip install -q datasets loralib sentencepiece
+!pip -q install bitsandbytes accelerate
+```
+```python
+from IPython.display import HTML, display
+def set_css():
+  display(HTML('''
+  <style>
+    pre {
+        white-space: pre-wrap;
+    }
+  </style>
+  '''))
+get_ipython().events.register('pre_run_cell', set_css)
+```
+```python
+import torch
+import transformers
+from transformers import AutoTokenizer, AutoModelForCausalLM
+model = AutoModelForCausalLM.from_pretrained(
+    "datatab/Yugo55A-GPT", torch_dtype="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained(
+    "datatab/Yugo55A-GPT", torch_dtype="auto"
+)
+```
+```python
+from typing import Optional
+from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
+def generate(
+    user_content: str, system_content: Optional[str] = ""
+) -> str:
+    system_content = "Ispod je uputstvo koje opisuje zadatak, upareno sa unosom koji pruža dodatni kontekst. Napišite odgovor koji na odgovarajući način kompletira zahtev."
+    messages = [
+        {
+            "role": "system",
+            "content": system_content,
+        },
+        {"role": "user", "content": user_content},
+    ]
+    tokenized_chat = tokenizer.apply_chat_template(
+        messages, tokenize=True, add_generation_prompt=True, return_tensors="pt"
+    ).to("cuda")
+    text_streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
+    output = model.generate(
+        tokenized_chat,
+        streamer=text_streamer,
+        max_new_tokens=2048,
+        temperature=0.1,
+        repetition_penalty=1.11,
+        top_p=0.92,
+        top_k=1000,
+        pad_token_id=tokenizer.pad_token_id,
+        eos_token_id=tokenizer.eos_token_id,
+        do_sample=True,
+    )
+    generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
+```
+```python
+generate("Nabroj mi sve planete suncevog sistemai reci mi koja je najveca planeta")
+```
+```python
+generate("Koja je razlika između lame, vikune i alpake?")
+```
+```python
+generate("Napišite kratku e-poruku Semu Altmanu dajući razloge za GPT-4 otvorenog koda")
+```