Instructions to use modelling101/CodeBERT-SO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use modelling101/CodeBERT-SO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="modelling101/CodeBERT-SO")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("modelling101/CodeBERT-SO") model = AutoModelForSequenceClassification.from_pretrained("modelling101/CodeBERT-SO", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from modelling101/CodeBERT-SO: direct link, hf CLI and curl.
- Browser
- Download file 2.11 MB
-
https://huggingface.co/modelling101/CodeBERT-SO/resolve/66c229abdc9f8bd6d40616e06abf3312e2fbcbca/tokenizer.json
- Command line
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hf download hf://modelling101/CodeBERT-SO@66c229abdc9f8bd6d40616e06abf3312e2fbcbca/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/modelling101/CodeBERT-SO/resolve/66c229abdc9f8bd6d40616e06abf3312e2fbcbca/tokenizer.json
2.11 MB
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