README.md

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# CT-LLM-Base
[**🌐 Homepage**](https://chinese-tiny-llm.github.io) | [**🤗 MAP-CC**](https://huggingface.co/datasets/m-a-p/MAP-CC) | [**🤗 CHC-Bench**](https://huggingface.co/datasets/m-a-p/CHC-Bench) | [**🤗 CT-LLM**](https://huggingface.co/collections/m-a-p/chinese-tiny-llm-660d0133dff6856f94ce0fc6) | [**📖 arXiv**](https://arxiv.org/abs/2404.04167) | [**GitHub**](https://github.com/Chinese-Tiny-LLM/Chinese-Tiny-LLM)

CT-LLM-Base is the first Chinese-centric large language model, both pre-training and fine-tuned primarily on Chinese corpora, and offers significant insights into potential biases, Chinese language ability, and multilingual adaptability.

## Uses

<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
```
from transformers import AutoModelForCausalLM, AutoTokenizer

model_path = '<your-model-path>'

tokenizer = AutoTokenizer.from_pretrained(model_path, use_fast=False, trust_remote_code=True)

model = AutoModelForCausalLM.from_pretrained(
    model_path,
    device_map="auto",
    torch_dtype='auto'
).eval()

input_text = "很久很久以前，"

input_ids = tokenizer(input_text, add_generation_prompt=True, return_tensors='pt').to(model.device)
output_ids = model.generate(**input_ids, max_new_tokens=20)
response = tokenizer.decode(output_ids[0], skip_special_tokens=True)

print(response)

```