Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use yangel88/text_classification_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yangel88/text_classification_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yangel88/text_classification_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yangel88/text_classification_model") model = AutoModelForSequenceClassification.from_pretrained("yangel88/text_classification_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7166e43176af8df7a46053c20f85ed9de5d912498dbd963e844e1d38ee5292f8
- Size of remote file:
- 268 MB
- SHA256:
- 1e2479a2faf132f05a87aa66e4fdb7121407a489568d0ee98d2a6ddd3f935e6d
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