Instructions to use giganticode/bert-base-StackOverflow-comments_2M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use giganticode/bert-base-StackOverflow-comments_2M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="giganticode/bert-base-StackOverflow-comments_2M")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("giganticode/bert-base-StackOverflow-comments_2M") model = AutoModelForMaskedLM.from_pretrained("giganticode/bert-base-StackOverflow-comments_2M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from giganticode/bert-base-StackOverflow-comments_2M: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/giganticode/bert-base-StackOverflow-comments_2M/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://giganticode/bert-base-StackOverflow-comments_2M/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/giganticode/bert-base-StackOverflow-comments_2M/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 10e1bcf0308499c3f47f03eed3ee9564da5967946c8c148407a8ebc90343ff66
- Size of remote file:
- 438 MB
- SHA256:
- 6357437d75036d2d57d6bc17ef79e7566c1cf43f68223e25ab3c7fcf5a490e3f
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