|
--- |
|
tags: |
|
- text-generation |
|
language: zh |
|
--- |
|
|
|
## Note |
|
|
|
**This repo is under development.** |
|
|
|
## Usage |
|
|
|
``` |
|
pip install transformers |
|
``` |
|
|
|
```python |
|
from transformers import CPMAntTokenizer, CPMAntForCausalLM |
|
|
|
texts = "今天天气不错，" |
|
model = CPMAntForCausalLM.from_pretrained("openbmb/cpm-ant-10b") |
|
tokenizer = CPMAntTokenizer.from_pretrained("openbmb/cpm-ant-10b") |
|
input_ids = tokenizer(texts, return_tensors="pt") |
|
outputs = model.generate(**input_ids) |
|
output_texts = tokenizer.batch_decode(outputs) |
|
|
|
print(output_texts) |
|
``` |
|
## pipeline |
|
```python |
|
texts = ["今天天气不错，"，"新年快乐，万事如意，"] |
|
generator = pipeline("text-generation", model="openbmb/cpm-ant-10b", tokenizer="openbmb/cpm-ant-10b") |
|
result = generator(texts) |
|
print(result) |
|
``` |
