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---
license: apache-2.0
datasets:
- BelleGroup/train_1M_CN
- BelleGroup/multiturn_chat_0.8M
- jeffwan/sharegpt_vicuna
language:
- zh
- en
library_name: transformers
pipeline_tag: text-generation
tags:
- chat
widget:
- text: "<Human>: Hello <eoh> <Assistant>:"
example_title: "Hello"
- text: "<Human>: 你好 <eoh> <Assistant>:"
example_title: "你好"
- text: "<Human>: What should I do if I can't sleep at night? <eoh> <Assistant>:"
example_title: "insomnia"
- text: "<Human>: 晚上睡不着应该怎么办? <eoh> <Assistant>:"
example_title: "失眠"
inference:
parameters:
temperature: 0.8
max_new_tokens: 128
---
# ChatBLOOM
ChatBLOOM是基于[BLOOM](https://huggingface.co/bigscience/bloom-1b7)(17亿参数)训练的中英双语对话语言模型,此模型为SFT版本。
详见[Github](https://github.com/NicholasCao/ChatBloom)。
ChatBLOOM is a Chinese-English bilingual dialogue language model trained based on [BLOOM](https://huggingface.co/bigscience/bloom-1b7) (1.7 billion parameters). This model is the SFT version.
See [Github](https://github.com/NicholasCao/ChatBloom) for details.
## Usage
```python
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig
tokenizer = AutoTokenizer.from_pretrained('nicholascao/chatbloom-1b7-sft')
tokenizer.pad_token_id = tokenizer.eos_token_id
model = AutoModelForCausalLM.from_pretrained('nicholascao/chatbloom-1b7-sft').half()
inputs = tokenizer('<Human>: Hello <eoh> <Assistant>:', return_tensors='pt').to(torch.cuda.current_device())
model.to(torch.cuda.current_device())
output = model.generate(**inputs, max_length=768, do_sample=True, temperature=0.8, top_k=50, early_stopping=True, repetition_penalty=1.1)
output = tokenizer.decode(output[0], skip_special_tokens=True)
print(output)
```
## Limitation and Usage Limits
我们使用的数据集(例如[BELLE](https://github.com/LianjiaTech/BELLE))要求开发人员仅将数据用于研究目的。
因此,不允许将我们的模型用于商业以及其他潜在的有害用途。
The datasets we used (e.g. [BELLE](https://github.com/LianjiaTech/BELLE)) require developers only use the data for research purposes.
Thus, commercial and other potentially harmful uses of our models are not allowed. |