Instructions to use patrickvonplaten/bert-testing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use patrickvonplaten/bert-testing with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="patrickvonplaten/bert-testing")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("patrickvonplaten/bert-testing") model = AutoModelForMaskedLM.from_pretrained("patrickvonplaten/bert-testing", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from patrickvonplaten/bert-testing: direct link, hf CLI and curl.
- Browser
- Download file 23 MB
-
https://huggingface.co/patrickvonplaten/bert-testing/resolve/refs%2Fpr%2F2/pytorch_model.bin
- Command line
-
hf download hf://patrickvonplaten/bert-testing@refs/pr/2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/patrickvonplaten/bert-testing/resolve/refs%2Fpr%2F2/pytorch_model.bin
23 MB
- Xet hash:
- c257be5567f79368e45a8077fb8f0260d89f72c2d63c97c8fbac9d23d0917486
- Size of remote file:
- 23 MB
- SHA256:
- 9580e1018b202f5a8f30facd9f6c0ac9ccb64ad3f853278843b89d2bc3d11e3d
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