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lightonai/RITA_l

sourceHugging Faceupdated 4y agoView on Hugging Face
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RITA-L

RITA is a family of autoregressive protein models, developed by a collaboration of Lighton, the OATML group at Oxford, and the Debbie Marks Lab at Harvard.

Model#Paramsd_modellayerslm loss uniref-100
Small85M768122.31
Medium300M1024242.01
**Large**680M1536241.82
XLarge1.2B2048241.70

For full results see our preprint: https://arxiv.org/abs/2205.05789

Usage

Instantiate a model like so:

python
from transformers import AutoModel, AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("lightonai/RITA_l, trust_remote_code=True")
tokenizer = AutoTokenizer.from_pretrained("lightonai/RITA_l")

for generation we support pipelines:

python
from transformers import pipeline
rita_gen = pipeline('text-generation', model=model, tokenizer=tokenizer)
sequences = rita_gen("MAB", max_length=20, do_sample=True, top_k=950, repetition_penalty=1.2, 
                     num_return_sequences=2, eos_token_id=2)
for seq in sequences:
    print(f"seq: {seq['generated_text'].replace(' ', '')}")

How to cite

@article{hesslow2022rita, title={RITA: a Study on Scaling Up Generative Protein Sequence Models}, author={Hesslow, Daniel and Zanichelli, Niccol{\'o} and Notin, Pascal and Poli, Iacopo and Marks, Debora}, journal={arXiv preprint arXiv:2205.05789}, year={2022} }