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") - Inference
- Notebooks
- Google Colab
- Kaggle
Download rust_model.ot from huggingface/CodeBERTa-language-id: direct link, hf CLI and curl.
- Browser
- Download file 336 MB
-
https://huggingface.co/huggingface/CodeBERTa-language-id/resolve/refs%2Fpr%2F7/rust_model.ot
- Command line
-
hf download hf://huggingface/CodeBERTa-language-id@refs/pr/7/rust_model.ot
-
curl -L -o rust_model.ot https://huggingface.co/huggingface/CodeBERTa-language-id/resolve/refs%2Fpr%2F7/rust_model.ot
336 MB
- Xet hash:
- 0c22b6b3282cd64ffcef9085cec4cf0e43cd4c8818c474ff88d727c1ec874ce8
- Size of remote file:
- 336 MB
- SHA256:
- be0359bfdb1893fb3bb7818fbaede7c5a37a5aba3996048c30977a552e95f2bd
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