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--- |
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license: apache-2.0 |
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tags: |
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- medical |
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--- |
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This repo contains PMC_LLaMA_7B, which is LLaMA-7b finetuned on the PMC papers in S2ORC dataset. |
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The model was trained with the following hyperparameters: |
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* Epochs: 5 |
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* Batch size: 128 |
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* Cutoff length: 512 |
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* Learning rate: 2e-5 |
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Each epoch we sample 512 tokens per paper for training. |
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The model can be loaded as following: |
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``` |
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import transformers |
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import torch |
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tokenizer = transformers.LlamaTokenizer.from_pretrained('chaoyi-wu/PMC_LLAMA_7B') |
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model = transformers.LlamaForCausalLM.from_pretrained('chaoyi-wu/PMC_LLAMA_7B') |
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sentence = 'Hello, doctor' |
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batch = tokenizer( |
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sentence, |
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return_tensors="pt", |
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add_special_tokens=False |
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) |
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with torch.no_grad(): |
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generated = model.generate(inputs = batch["input_ids"], max_length=200, do_sample=True, top_k=50) |
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print('model predict: ',tokenizer.decode(generated[0])) |
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``` |
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