Edit model card

Mirror of the base ProGen2-base model (with slightly modified configuration and forward pass) by Nijkamp, et al..

See also my github repo for an example of finetuning this model.

Example usage:

from transformers import AutoModelForCausalLM
from tokenizers import Tokenizer
import torch
import torch.nn.functional as F

# load model and tokenizer
model = AutoModelForCausalLM.from_pretrained("hugohrban/progen2-base", trust_remote_code=True)
tokenizer = Tokenizer.from_pretrained("hugohrban/progen2-base")
tokenizer.no_padding()

# prepare input
prompt = "1MEVVIVTGMSGAGK"
input_ids = torch.tensor(tokenizer.encode(prompt).ids).to(model.device)

# forward pass
logits = model(input_ids).logits

# print output probabilities
next_token_logits = logits[-1, :]
next_token_probs = F.softmax(next_token_logits, dim=-1)
for i in range(tokenizer.get_vocab_size(with_added_tokens=False)):
    print(f"{tokenizer.id_to_token(i)}: {100 * next_token_probs[i].item():.2f} %")
Downloads last month
2,150
Safetensors
Model size
765M params
Tensor type
F32
ยท
Inference Examples
Inference API (serverless) does not yet support model repos that contain custom code.

Space using hugohrban/progen2-base 1