Instructions to use michaelfeil/ct2fast-falcon-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use michaelfeil/ct2fast-falcon-7b with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("michaelfeil/ct2fast-falcon-7b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.bin from michaelfeil/ct2fast-falcon-7b: direct link, hf CLI and curl.
- Browser
- Download file 6.93 GB
-
https://huggingface.co/michaelfeil/ct2fast-falcon-7b/resolve/main/model.bin
- Command line
-
hf download hf://michaelfeil/ct2fast-falcon-7b/model.bin
-
curl -L -o model.bin https://huggingface.co/michaelfeil/ct2fast-falcon-7b/resolve/main/model.bin
6.93 GB
- Xet hash:
- 9971d7d11c58ea210ad30b7317aef3a714043f63e65a977b50d560c71b2bd30b
- Size of remote file:
- 6.93 GB
- SHA256:
- 3d6bdff77f55283dfab9dbdf3fcad65f991504f22303971bf475b64245e34397
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.