Instructions to use giganticode/bert-base-code_comments with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use giganticode/bert-base-code_comments with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="giganticode/bert-base-code_comments")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("giganticode/bert-base-code_comments") model = AutoModelForMaskedLM.from_pretrained("giganticode/bert-base-code_comments", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from giganticode/bert-base-code_comments: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/giganticode/bert-base-code_comments/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://giganticode/bert-base-code_comments@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/giganticode/bert-base-code_comments/resolve/refs%2Fpr%2F1/model.safetensors
438 MB
- Xet hash:
- 44c971a8183dd0f107b4282c388f112d0f159922badd04ffab3cf28038e6f062
- Size of remote file:
- 438 MB
- SHA256:
- 6c663b277e26e04a9833b166c8c079da27c35ff8814ff40cec151259d414d77c
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