Instructions to use huggingface/CodeBERTa-language-id with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use huggingface/CodeBERTa-language-id with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="huggingface/CodeBERTa-language-id")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("huggingface/CodeBERTa-language-id") model = AutoModelForSequenceClassification.from_pretrained("huggingface/CodeBERTa-language-id", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from huggingface/CodeBERTa-language-id: direct link, hf CLI and curl.
- Browser
- Download file 336 MB
-
https://huggingface.co/huggingface/CodeBERTa-language-id/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://huggingface/CodeBERTa-language-id/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/huggingface/CodeBERTa-language-id/resolve/main/pytorch_model.bin
336 MB
- Xet hash:
- 98b0721a3167f401c648ae67be836f3a3ad84909c78464e31c2f81ca0b083deb
- Size of remote file:
- 336 MB
- SHA256:
- 4519a031ac532918a4b9b2ca9633d05e37ed3f68f52e7cf327ef94408d1d28a1
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