metadata

license: mit
language:
  - ru
pipeline_tag: text2text-generation
widget:
  - text: '<SC6>Человек: Ответь на вопрос. Почему трава зеленая?\nБот: <extra_id_0>'

Den4ikAI/FRED-T5-XL_instructor

Инструкционная модель на FRED-T5-XL.

Пример использования

from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
import torch
use_cuda = torch.cuda.is_available()
device = torch.device("cuda" if use_cuda else "cpu")
tokenizer = AutoTokenizer.from_pretrained("Den4ikAI/FRED-T5-XL_instructor")
model = AutoModelForSeq2SeqLM.from_pretrained("Den4ikAI/FRED-T5-XL_instructor", torch_dtype=torch.float16).to(device)
model.eval()

from transformers import GenerationConfig

generation_config = GenerationConfig.from_pretrained("Den4ikAI/FRED-T5-XL_instructor")
def generate(prompt):
  data = tokenizer(f"<SC6>Человек: {prompt}\nБот: <extra_id_0>", return_tensors="pt").to(model.device)
  output_ids = model.generate(
      **data,
      generation_config=generation_config
  )[0]
  print(tokenizer.decode(data["input_ids"][0].tolist()))
  out = tokenizer.decode(output_ids.tolist())
  return out

while 1:
  generate(input(":> "))

Citation

@MISC{Den4ikAI/FRED-T5-XL_instructor,
    author  = {Denis Petrov},
    title   = {Russian Instructor Model},
    url     = {https://huggingface.co./Den4ikAI/FRED-T5-XL_instructor/},
    year    = 2023
}