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--- |
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library_name: transformers |
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license: apache-2.0 |
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--- |
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# Model card for MisterUkrainianDPO |
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DPO Iteration of [MisterUkrainian](https://huggingface.co/Radu1999/MisterUkrainian) |
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## Instruction format |
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In order to leverage instruction fine-tuning, your prompt should be surrounded by `[INST]` and `[/INST]` tokens. |
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E.g. |
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``` |
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text = "[INST]Відповідайте лише буквою правильної відповіді: Елементи експресіонізму наявні у творі: A. «Камінний хрест», B. «Інститутка», C. «Маруся», D. «Людина»[/INST]" |
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``` |
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This format is available as a [chat template](https://huggingface.co/docs/transformers/main/chat_templating) via the `apply_chat_template()` method: |
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## Model Architecture |
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This instruction model is based on Mistral-7B-v0.2, a transformer model with the following architecture choices: |
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- Grouped-Query Attention |
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- Sliding-Window Attention |
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- Byte-fallback BPE tokenizer |
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## 💻 Usage |
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```python |
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!pip install -qU transformers 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 = "Radu1999/MisterUkrainianDPO" |
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messages = [{"role": "user", "content": "What is a large language model?"}] |
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tokenizer = AutoTokenizer.from_pretrained(model) |
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prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) |
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pipeline = transformers.pipeline( |
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"text-generation", |
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model=model, |
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torch_dtype=torch.bfloat16, |
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device_map="auto", |
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) |
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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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## Author |
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Radu Chivereanu |
