PMC_LLAMA_7B_10_epoch

This repo contains the latest version of PMC_LLaMA_7B, which is LLaMA-7b finetuned on the PMC papers in the S2ORC dataset.

Notably, different from chaoyi-wu/PMC_LLAMA_7B, this model is further trained for 10 epochs.

The model was trained with the following hyperparameters:

• Epochs: 10
• Batch size: 128
• Cutoff length: 512
• Learning rate: 2e-5

Each epoch we sample 512 tokens per paper for training.

The model can be loaded as follows:

import transformers
import torch
tokenizer = transformers.LlamaTokenizer.from_pretrained('chaoyi-wu/PMC_LLAMA_7B_10_epoch')
model = transformers.LlamaForCausalLM.from_pretrained('chaoyi-wu/PMC_LLAMA_7B_10_epoch')
sentence = 'Hello, doctor' 
batch = tokenizer(
            sentence,
            return_tensors="pt", 
            add_special_tokens=False
        )
with torch.no_grad():
    generated = model.generate(inputs = batch["input_ids"], max_length=200, do_sample=True, top_k=50)
    print('model predict: ',tokenizer.decode(generated[0]))