Instructions to use google/fnet-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/fnet-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("google/fnet-base") model = AutoModelForPreTraining.from_pretrained("google/fnet-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from google/fnet-base: direct link, hf CLI and curl.
- Browser
- Download file 334 MB
-
https://huggingface.co/google/fnet-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://google/fnet-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/google/fnet-base/resolve/main/pytorch_model.bin
334 MB
- Xet hash:
- 075f4bf94b20c1ae4252d2eb4adca5aee6378c12717ece3838d2b870b8595e9a
- Size of remote file:
- 334 MB
- SHA256:
- a83d296a9a59b09e537a97d99b2fd58c1706f7137ede7ea6197ed122dbf713ae
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