48 lines
1.3 KiB
Markdown
48 lines
1.3 KiB
Markdown
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---
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license: apache-2.0
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datasets:
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- Intel/orca_dpo_pairs
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- nvidia/HelpSteer
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- jondurbin/truthy-dpo-v0.1
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language:
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- en
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library_name: transformers
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pipeline_tag: text-generation
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---
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### Mistral-7B-Forest-DPO
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Introducing Mistral-7B-Forest-DPO, a LLM fine-tuned with base model mistralai/Mistral-7B-v0.1, using direct preference optimization.
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This model showcases exceptional prowess across a spectrum of natural language processing (NLP) tasks.
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A mixture of the following datasets was used for fine-tuning.
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1. Intel/orca_dpo_pairs
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2. nvidia/HelpSteer
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3. jondurbin/truthy-dpo-v0.1
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💻 Usage
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```python
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!pip install -qU transformers bitsandbytes accelerate
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from transformers import AutoTokenizer
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import transformers
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import torch
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model = "abhishekchohan/mistral-7B-forest-dpo"
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tokenizer = AutoTokenizer.from_pretrained(model)
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pipeline = transformers.pipeline(
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"text-generation",
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model=model,
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model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
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)
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messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
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prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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print(outputs[0]["generated_text"])
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```
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