Instructions to use michaelfeil/ct2fast-falcon-7b-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use michaelfeil/ct2fast-falcon-7b-instruct with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("michaelfeil/ct2fast-falcon-7b-instruct", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.bin from michaelfeil/ct2fast-falcon-7b-instruct: direct link, hf CLI and curl.
- Browser
- Download file 6.93 GB
-
https://huggingface.co/michaelfeil/ct2fast-falcon-7b-instruct/resolve/main/model.bin
- Command line
-
hf download hf://michaelfeil/ct2fast-falcon-7b-instruct/model.bin
-
curl -L -o model.bin https://huggingface.co/michaelfeil/ct2fast-falcon-7b-instruct/resolve/main/model.bin
6.93 GB
- Xet hash:
- 92f368cb8475171cd5a3ccfa35f7bc0069ba0b4cde5ac8bb748ebbb3a2bfe167
- Size of remote file:
- 6.93 GB
- SHA256:
- 3f18407937173d51d0b039e48080fc923b5f0871b86329e8629274ed5f27e18e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.