Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use cnicu/product_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cnicu/product_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cnicu/product_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cnicu/product_classifier") model = AutoModelForSequenceClassification.from_pretrained("cnicu/product_classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e8b31dc10d1afa5ca6ffdd700d86a92c5642da24b5983595623c7021d34207a0
- Size of remote file:
- 3.58 kB
- SHA256:
- 90f43b6cdcc08ceb730281167560169d674aba6b301d91b606fafcc664da939d
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