Instructions to use hf-internal-testing/tiny-random-FNetForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FNetForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-FNetForMaskedLM")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-FNetForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-FNetForMaskedLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-internal-testing/tiny-random-FNetForMaskedLM: direct link, hf CLI and curl.
- Browser
- Download file 4.38 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-FNetForMaskedLM/resolve/09dbff8261adf5c5830aa254e2c35f0956c879ec/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-FNetForMaskedLM@09dbff8261adf5c5830aa254e2c35f0956c879ec/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-FNetForMaskedLM/resolve/09dbff8261adf5c5830aa254e2c35f0956c879ec/pytorch_model.bin
4.38 MB
- Xet hash:
- 34d451e7ad64e8464cd0a44f0eabc788f5a73584c5935491dfd5f339daa6c15c
- Size of remote file:
- 4.38 MB
- SHA256:
- a60dcb6aed4f65023e36d84c0c3b3b26af68dbb78f67b2e2f5a9888cf3c09158
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