|
--- |
|
license: mit |
|
widget: |
|
- text: |- |
|
<SC1>- как ты? |
|
- <extra_id_0> |
|
example_title: how r u |
|
language: |
|
- ru |
|
pipeline_tag: text2text-generation |
|
--- |
|
|
|
# Usage |
|
|
|
```python |
|
import torch |
|
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM |
|
|
|
device = "cuda" |
|
|
|
tokenizer = AutoTokenizer.from_pretrained('TeraSpace/dialofred') |
|
model = AutoModelForSeq2SeqLM.from_pretrained('TeraSpace/dialofred', device_map=device)# Add torch_dtype=torch.bfloat16 to use less memory |
|
while True: |
|
text_inp = input("=>") |
|
lm_text=f'<SC1>- {text_inp}\n- <extra_id_0>' |
|
input_ids=torch.tensor([tokenizer.encode(lm_text)]).to(model.device) |
|
# outputs=model.generate(input_ids=input_ids, |
|
# max_length=200, |
|
# eos_token_id=tokenizer.eos_token_id, |
|
# early_stopping=True, |
|
# do_sample=True, |
|
# temperature=1.0, |
|
# top_k=0, |
|
# top_p=0.85) |
|
# outputs=model.generate(input_ids,eos_token_id=tokenizer.eos_token_id,early_stopping=True) |
|
outputs=model.generate(input_ids=input_ids, |
|
max_length=200, |
|
eos_token_id=tokenizer.eos_token_id, |
|
early_stopping=True, |
|
do_sample=True, |
|
temperature=0.7, |
|
top_k=0, |
|
top_p=0.8) |
|
|
|
print(tokenizer.decode(outputs[0][1:])) |
|
``` |
