Instructions to use hf-tiny-model-private/tiny-random-FNetForPreTraining with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-FNetForPreTraining with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-FNetForPreTraining") model = AutoModelForPreTraining.from_pretrained("hf-tiny-model-private/tiny-random-FNetForPreTraining", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-tiny-model-private/tiny-random-FNetForPreTraining: direct link, hf CLI and curl.
- Browser
- Download file 4.38 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-FNetForPreTraining/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-FNetForPreTraining/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-tiny-model-private/tiny-random-FNetForPreTraining/resolve/main/pytorch_model.bin
4.38 MB
- Xet hash:
- 0d4175b08008c465dbb683bf2a9d71eeb8daecde200cf77309592e9c6d1a6759
- Size of remote file:
- 4.38 MB
- SHA256:
- 332721f6cf1b8c5b68d2962343be6060932535abfd0662815cc498f848ed265e
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