Instructions to use giganticode/bert-large-StackOverflow-comments_1M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use giganticode/bert-large-StackOverflow-comments_1M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="giganticode/bert-large-StackOverflow-comments_1M")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("giganticode/bert-large-StackOverflow-comments_1M") model = AutoModelForMaskedLM.from_pretrained("giganticode/bert-large-StackOverflow-comments_1M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from giganticode/bert-large-StackOverflow-comments_1M: direct link, hf CLI and curl.
- Browser
- Download file 1.34 GB
-
https://huggingface.co/giganticode/bert-large-StackOverflow-comments_1M/resolve/d1663e84f1e58cfdf0325418903972f9aca2ea71/pytorch_model.bin
- Command line
-
hf download hf://giganticode/bert-large-StackOverflow-comments_1M@d1663e84f1e58cfdf0325418903972f9aca2ea71/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/giganticode/bert-large-StackOverflow-comments_1M/resolve/d1663e84f1e58cfdf0325418903972f9aca2ea71/pytorch_model.bin
1.34 GB
- Xet hash:
- 5b5dba7e92b42888c0613fb29161ef58559fe756929472a987d2a21e10669057
- Size of remote file:
- 1.34 GB
- SHA256:
- 9877a167a83ebd0b0e22f3a11d80850d2059063d2c100d9aeda00a69ea171890
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