Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use PracticalWork/distilbert-base-uncased-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PracticalWork/distilbert-base-uncased-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PracticalWork/distilbert-base-uncased-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PracticalWork/distilbert-base-uncased-classifier") model = AutoModelForSequenceClassification.from_pretrained("PracticalWork/distilbert-base-uncased-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d980c5b2ea4f4821b8578c76a0ed817275e032111fc48bd0cab0da978e0dd7de
- Size of remote file:
- 268 MB
- SHA256:
- c72b1940029f65c23bbd5d92974270f196850a4a9949d197d87144838d72f61e
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