Instructions to use slh/fcnet-base-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use slh/fcnet-base-cased with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import fcnet model = fcnet.from_pretrained("slh/fcnet-base-cased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from slh/fcnet-base-cased: direct link, hf CLI and curl.
- Browser
- Download file 4.81 MB
-
https://huggingface.co/slh/fcnet-base-cased/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://slh/fcnet-base-cased/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/slh/fcnet-base-cased/resolve/main/pytorch_model.bin
4.81 MB
- Xet hash:
- b6f9415c659e782d6e89569b4f70c8ef5f1daedb326f5c414f409234450a2d18
- Size of remote file:
- 4.81 MB
- SHA256:
- d5ae69dd1a5f2d87875eb48c3d5933a6b47be6d0aff9fe8bf57629e9b2ea0968
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