Instructions to use Ct1tz/Codebert-Base-B2D4G5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ct1tz/Codebert-Base-B2D4G5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ct1tz/Codebert-Base-B2D4G5")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ct1tz/Codebert-Base-B2D4G5") model = AutoModelForSequenceClassification.from_pretrained("Ct1tz/Codebert-Base-B2D4G5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 21f117013174d8845a2ff2d35e9f6b4ad4ee38be9f6574a71b0d1f4170d9ddb3
- Size of remote file:
- 5.24 kB
- SHA256:
- 63651316137ef8a43b7b68fffe153c9c989f961f0e3702d3b3c782028c356ff2
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