--- 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: ": Hello :" example_title: "Hello" - text: ": 你好 :" example_title: "你好" - text: ": What should I do if I can't sleep at night? :" example_title: "insomnia" - text: ": 晚上睡不着应该怎么办? :" 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 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(': Hello :', 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.