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 flax_model.msgpack from patrickvonplaten/bert-testing: direct link, hf CLI and curl.
- Browser
- Download file 22.9 MB
-
https://huggingface.co/patrickvonplaten/bert-testing/resolve/refs%2Fpr%2F1/flax_model.msgpack
- Command line
-
hf download hf://patrickvonplaten/bert-testing@refs/pr/1/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/patrickvonplaten/bert-testing/resolve/refs%2Fpr%2F1/flax_model.msgpack
22.9 MB
- Xet hash:
- 83748acc78e694b3f643bca533e38b5af0116efed965879e4847fe02df0aa59c
- Size of remote file:
- 22.9 MB
- SHA256:
- b1bd48f134108bdce6ebed6716fbd56523212443803ab395b4900714dbb92984
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