Instructions to use neulab/codebert-python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use neulab/codebert-python with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="neulab/codebert-python")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("neulab/codebert-python") model = AutoModelForMaskedLM.from_pretrained("neulab/codebert-python", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from neulab/codebert-python: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/neulab/codebert-python/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://neulab/codebert-python/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/neulab/codebert-python/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 2984b4649d028e5a59cb4ab21b8f07671c89935f0e0ee16442e9c79502377a57
- Size of remote file:
- 499 MB
- SHA256:
- 8130e8739f247fae8076d2c193f2363bbc6b88b391c1269448565a6d13c8842a
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