Table Question Answering
Transformers
PyTorch
English
llama
text-generation
text-generation-inference
Instructions to use bragour/Camel-7b-chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bragour/Camel-7b-chat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("table-question-answering", model="bragour/Camel-7b-chat")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("bragour/Camel-7b-chat") model = AutoModelForCausalLM.from_pretrained("bragour/Camel-7b-chat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from bragour/Camel-7b-chat: direct link, hf CLI and curl.
- Browser
- Download file 1.84 MB
-
https://huggingface.co/bragour/Camel-7b-chat/resolve/main/tokenizer.json
- Command line
-
hf download hf://bragour/Camel-7b-chat/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/bragour/Camel-7b-chat/resolve/main/tokenizer.json
1.84 MB
File too large to display, you can check the raw version instead.