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 model.safetensors from hf-internal-testing/tiny-random-FNetModel: direct link, hf CLI and curl.
- Browser
- Download file 4.23 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-FNetModel/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-FNetModel@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-FNetModel/resolve/refs%2Fpr%2F1/model.safetensors
4.23 MB
- Xet hash:
- 377e421acc2d403d5777d75d2ad92b9300a1afe0377de03967290bb4135f3223
- Size of remote file:
- 4.23 MB
- SHA256:
- 5c1b648437207d58b5861409696b9cf1ea3283fa18a68b877bfb01ec89f1aa38
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