Instructions to use hf-internal-testing/tiny-random-FNetModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FNetModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-FNetModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-FNetModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-FNetModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-internal-testing/tiny-random-FNetModel: direct link, hf CLI and curl.
- Browser
- Download file 278 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-FNetModel/resolve/38041395aa488da543dec9ed86318d9ec4d4839e/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-FNetModel@38041395aa488da543dec9ed86318d9ec4d4839e/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-FNetModel/resolve/38041395aa488da543dec9ed86318d9ec4d4839e/pytorch_model.bin
278 kB
- Xet hash:
- e0600b6574e261d2ac03204ccd8765386589210671e4f6b8711bf572d0976cbc
- Size of remote file:
- 278 kB
- SHA256:
- 08a3381c0227c7bbd0b12ee4a505af9d28dd45a6ed5b4f5567c614638505a5ac
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