Question Answering
Transformers
Safetensors
Chinese
English
llama
text-generation
custom_code
text-generation-inference
Instructions to use FlagAlpha/Atom-7B-Chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FlagAlpha/Atom-7B-Chat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="FlagAlpha/Atom-7B-Chat", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("FlagAlpha/Atom-7B-Chat", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("FlagAlpha/Atom-7B-Chat", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
该模型与 FlagAlpha/Llama2-Chinese-7b-Chat 之间是什么关系?有什么区别?
#3
by yyqqing - opened
该模型与 FlagAlpha/Llama2-Chinese-7b-Chat 之间是什么关系?有什么区别?
FlagAlpha/Llama2-Chinese-7b-Chat 是基于llama2 做了中文的微调。当前版本是结合了中文的数据进行了预训练并对话微调、强化学习。这个版本是对于中文效果最好的。
该模型与 FlagAlpha/Llama2-Chinese-7b-Chat 之间是什么关系?有什么区别?
FlagAlpha/Llama2-Chinese-7b-Chat 是基于llama2 做了中文的微调。当前版本是结合了中文的数据进行了预训练并对话微调、强化学习。这个版本是对于中文效果最好的。