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:
- 87b6aad37c74797469942c321029b34beb120075ba21d96a505d1d9e42b97147
- Size of remote file:
- 4.09 kB
- SHA256:
- 61fdc5e8b8f5e1b6744dd4dba8d9134e356e77be97b2cc87e352587936a1e954
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