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 tf_model.h5 from huggingface/CodeBERTa-language-id: direct link, hf CLI and curl.
- Browser
- Download file 334 MB
-
https://huggingface.co/huggingface/CodeBERTa-language-id/resolve/refs%2Fpr%2F7/tf_model.h5
- Command line
-
hf download hf://huggingface/CodeBERTa-language-id@refs/pr/7/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/huggingface/CodeBERTa-language-id/resolve/refs%2Fpr%2F7/tf_model.h5
334 MB
- Xet hash:
- 90a15c06aefb62edea068aba428dc91f12080814d7ee0baf044fbfc0cd1a34fa
- Size of remote file:
- 334 MB
- SHA256:
- 9114ffaf2db4344a1e463f0713177ab811b8c141746090144a9e3e8b52155890
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