Instructions to use faizack/bert-finetuned-quick-tutorial with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use faizack/bert-finetuned-quick-tutorial with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="faizack/bert-finetuned-quick-tutorial")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("faizack/bert-finetuned-quick-tutorial") model = AutoModelForMaskedLM.from_pretrained("faizack/bert-finetuned-quick-tutorial", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from faizack/bert-finetuned-quick-tutorial: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/faizack/bert-finetuned-quick-tutorial/resolve/main/model.safetensors
- Command line
-
hf download hf://faizack/bert-finetuned-quick-tutorial/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/faizack/bert-finetuned-quick-tutorial/resolve/main/model.safetensors
438 MB
- Xet hash:
- 821dcb29ec153a9988a005e053868aa311ef3344b73fa57c8796d9b9018db6ed
- Size of remote file:
- 438 MB
- SHA256:
- 8fcebeb4076c128614e0a887b2008b2be082904c75f1a223a731126b490a36d0
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