Instructions to use DPhO05/codebert-tesoro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DPhO05/codebert-tesoro with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DPhO05/codebert-tesoro")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DPhO05/codebert-tesoro") model = AutoModelForSequenceClassification.from_pretrained("DPhO05/codebert-tesoro") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 85a3afc74156535518160080818ee668f60173d9ed8a796bfa6cf48282134880
- Size of remote file:
- 499 MB
- SHA256:
- 35d10185df4f8081a346977b3e1b9359af9ec111cb92d8ad0827cadbaa21395d
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