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:
- 4a428fe77e2f7ae936b29a961999e884160b0fe085c158fd3ce56610a10ad1ac
- Size of remote file:
- 997 MB
- SHA256:
- e62dc2d191b49cee9fd815ec78acb9c7a579b2a37b2b1d7f8aa6375ca3a0e23a
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