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--- |
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license: apache-2.0 |
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datasets: |
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- mlabonne/mini-platypus |
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pipeline_tag: text-generation |
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--- |
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# 🦙🧠 Miniplatypus-7b |
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<center><img src="https://i.imgur.com/VkGvQym.png" width="300"></center> |
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This is a `Llama-2-7b-chat` model fine-tuned using QLoRA (4-bit precision) on the [`mlabonne/guanaco-llama2-1k`](https://huggingface.co/datasets/mlabonne/mini-platypus) dataset, which is a subset of the [`garage-bAInd/Open-Platypus`](https://huggingface.co/datasets/garage-bAInd/Open-Platypus). |
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## 🔧 Training |
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It was trained on a Google Colab notebook with a T4 GPU. It is mainly designed for educational purposes, not for inference. |
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## 💻 Usage |
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``` python |
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# pip install 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 = "mlabonne/llama-2-7b-miniplatypus" |
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prompt = "What is a large language model?" |
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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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torch_dtype=torch.float16, |
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device_map="auto", |
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) |
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sequences = pipeline( |
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f'<s>[INST] {prompt} [/INST]', |
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do_sample=True, |
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top_k=10, |
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num_return_sequences=1, |
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eos_token_id=tokenizer.eos_token_id, |
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max_length=200, |
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) |
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for seq in sequences: |
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print(f"Result: {seq['generated_text']}") |
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``` |
