BioMedLM

Code used for pre-training and fine-tuning the BioMedLM model.

Note: This model was previously known as PubMedGPT, but the NIH has asked us to change the name since they hold the trademark on "PubMed", so the new name is BioMedLM!

Links

Blog

Model

MosaicML Composer

Example Usage

import torch

from transformers import GPT2LMHeadModel, GPT2Tokenizer

device = torch.device("cuda")

tokenizer = GPT2Tokenizer.from_pretrained("stanford-crfm/BioMedLM")

model = GPT2LMHeadModel.from_pretrained("stanford-crfm/BioMedLM").to(device)

input_ids = tokenizer.encode(
    "Photosynthesis is ", return_tensors="pt"
).to(device)

sample_output = model.generate(input_ids, do_sample=True, max_length=50, top_k=50)

print("Output:\n" + 100 * "-")
print(tokenizer.decode(sample_output[0], skip_special_tokens=True))