Instructions to use stephen423/bert-base-cased-wikitext2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stephen423/bert-base-cased-wikitext2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="stephen423/bert-base-cased-wikitext2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("stephen423/bert-base-cased-wikitext2") model = AutoModelForMaskedLM.from_pretrained("stephen423/bert-base-cased-wikitext2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from stephen423/bert-base-cased-wikitext2: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/stephen423/bert-base-cased-wikitext2/resolve/main/training_args.bin
- Command line
-
hf download hf://stephen423/bert-base-cased-wikitext2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/stephen423/bert-base-cased-wikitext2/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- a5bf40d8da310f676d2f87f05eeeb99eb44b1a99a3cde0ff6a8a21828c0a2004
- Size of remote file:
- 4.09 kB
- SHA256:
- 8bd9f457bfa373d8501ac68ccb60046647a3540b0a608c4d11ee6f3a03ad1e60
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