Create README.md

README.md

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+---
+license: cc-by-nc-4.0
+base_model: mlabonne/Monarch-7B
+datasets:
+- yleo/emerton_dpo_pairs_judge
+tags:
+- dpo
+---
+---
+
+# 🦜 EmertonMonarch-7B
+
+EmertonOmniBeagle-7B-dpo is a DPO fine-tune of [mlabonne/Monarch-7B](https://huggingface.co/mlabonne/OmniBeagle-7B) using the [yleo/emerton_dpo_pairs_judge](https://huggingface.co/datasets/yleo/emerton_dpo_pairs_judge) preference dataset created from [Intel/orca_dpo_pairs](https://huggingface.co/datasets/Intel/orca_dpo_pairs) by replacing gpt 3.5 answer by a gpt4 Turbo answer. Then, gpt4 Turbo is put as chosen whereas gpt4 is put as rejected.
+
+## 🔍 Applications
+
+This model uses a context window of 8k. It is compatible with different templates, like chatml and Llama's chat template.
+
+## 🏆 Evaluation
+
+### Open LLM Leaderboard
+
+To come...
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+from transformers import AutoTokenizer
+import transformers
+import torch
+model = "yleo/EmertonBeagle-7B"
+messages = [{"role": "user", "content": "How to improve LLM fine-tuning?"}]
+tokenizer = AutoTokenizer.from_pretrained(model)
+prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+pipeline = transformers.pipeline(
+"text-generation",
+model=model,
+torch_dtype=torch.float16,
+device_map="auto",
+)
+outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+print(outputs[0]["generated_text"])
+```