Instructions to use Jinchen/bert-base-cased-wikitext2-test-mlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jinchen/bert-base-cased-wikitext2-test-mlm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Jinchen/bert-base-cased-wikitext2-test-mlm")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Jinchen/bert-base-cased-wikitext2-test-mlm") model = AutoModelForMaskedLM.from_pretrained("Jinchen/bert-base-cased-wikitext2-test-mlm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Jinchen/bert-base-cased-wikitext2-test-mlm: direct link, hf CLI and curl.
- Browser
- Download file 2.67 kB
-
https://huggingface.co/Jinchen/bert-base-cased-wikitext2-test-mlm/resolve/main/training_args.bin
- Command line
-
hf download hf://Jinchen/bert-base-cased-wikitext2-test-mlm/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/Jinchen/bert-base-cased-wikitext2-test-mlm/resolve/main/training_args.bin
2.67 kB
- Xet hash:
- dac14b9f72b27a841e15ad1f55951b9e16aca69454f1b1c3a888b2116cf2c86a
- Size of remote file:
- 2.67 kB
- SHA256:
- 5e58bc4b0cfe47d5441b045ed5380b648c488880d525fc409cb24e44d550904b
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