Question Answering
Transformers
PyTorch
Chinese
English
llama
text-generation
text-generation-inference
Instructions to use FlagAlpha/Llama2-Chinese-7b-Chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FlagAlpha/Llama2-Chinese-7b-Chat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="FlagAlpha/Llama2-Chinese-7b-Chat")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("FlagAlpha/Llama2-Chinese-7b-Chat") model = AutoModelForCausalLM.from_pretrained("FlagAlpha/Llama2-Chinese-7b-Chat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d89969098f1f1120f38d967ca5a082ff42345ce085d0a2c27ec33a0cbee3c0a5
- Size of remote file:
- 3.5 GB
- SHA256:
- db985e24dd56db66ca64fec483a3c8613bef661f43c9142bd895a0fb4d093360
Β·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.