Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Eitanli/website_classification_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Eitanli/website_classification_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Eitanli/website_classification_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Eitanli/website_classification_model") model = AutoModelForSequenceClassification.from_pretrained("Eitanli/website_classification_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b3ef50f7876c3b86b1860566da0fdc632fbd3338038deb1c2d9653fea95b5128
- Size of remote file:
- 268 MB
- SHA256:
- 4ac0000861196f00e91fb37e930ec516d0c427d53caa9698d3a54af3fd889c83
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