transformers safetensors t5 text2text-generation license:mit autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: mit
---

## Usage
```
def qa(doc, q):
  doc = doc.replace('\n',' ')
  q = q.replace('\n',' ')
  q_pr = f'<SC6>Опираясь на информацию: {doc}\n ответь на вопрос: \"{q}\".\n Ответ: '
  data_inp = tokenizer(q_pr, return_tensors="pt").to('cuda:0')
  return data_inp

def generate(doc, q):
  t = qa(doc, q)
  output_ids = model.generate(
      **t,  do_sample=False, temperature=0.0, max_new_tokens=512, repetition_penalty=1, no_repeat_ngram_size=8
  )[0]
  out = tokenizer.decode(output_ids.tolist(), skip_special_tokens=True)
  out = out.replace("<extra_id_0>","")
  ans_sqs = sent_tokenize(out, language="russian")
  ans = ' '.join(ans_sqs[:3])
  return ans.split('Ответ:')[0].split('Вопрос:')[0]
```
