|
--- |
|
language: |
|
- zh |
|
tags: |
|
- text generation |
|
- pytorch |
|
- causal-lm |
|
license: apache-2.0 |
|
--- |
|
|
|
# Mengzi-GPT-neo model (Chinese) |
|
Pretrained model on 300G Chinese corpus. |
|
|
|
## Usage |
|
```python |
|
import torch |
|
import sentencepiece as spm |
|
from transformers import GPTNeoForCausalLM |
|
tokenizer = spm.SentencePieceProcessor(model_file="mengzi_gpt.model") |
|
model = GPTNeoForCausalLM.from_pretrained("Langboat/mengzi-gpt-neo-base") |
|
|
|
def lm(prompt, top_k, top_p, max_length, repetition_penalty): |
|
input_ids = torch.tensor(tokenizer.encode([prompt]), dtype=torch.long, device='cuda') |
|
gen_tokens = model.generate( |
|
input_ids, |
|
do_sample=True, |
|
top_k=top_k, |
|
top_p=top_p, |
|
max_length=max_length+len(prompt), |
|
repetition_penalty=repetition_penalty) |
|
result = tokenizer.decode(gen_tokens.tolist())[0] |
|
return result |
|
``` |
|
|
