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/91eaae1eac894af5d96c0221ec9bcef7f1af41c8/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-FNetForMaskedLM@91eaae1eac894af5d96c0221ec9bcef7f1af41c8/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-FNetForMaskedLM/resolve/91eaae1eac894af5d96c0221ec9bcef7f1af41c8/pytorch_model.bin
4.38 MB
- Xet hash:
- 8e4f0cc68503c62c1c58bd1b1e108c452401c856571e7f2113d8a10c32cee053
- Size of remote file:
- 4.38 MB
- SHA256:
- 442eacd8de587613eb54550c1ef399f9e655385bdb735f39960627dee0184a5f
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