Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use abdelkader/distilbert-base-uncased-distilled-clinc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abdelkader/distilbert-base-uncased-distilled-clinc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="abdelkader/distilbert-base-uncased-distilled-clinc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("abdelkader/distilbert-base-uncased-distilled-clinc") model = AutoModelForSequenceClassification.from_pretrained("abdelkader/distilbert-base-uncased-distilled-clinc") - Notebooks
- Google Colab
- Kaggle
Add evaluation results on clinc_oos dataset
#1
by autoevaluator HF Staff - opened
Beep boop, I am a bot from Hugging Face's automatic model evaluator π!
Your model has been evaluated on the clinc_oos dataset by @lewtun , using the predictions stored here.
Accept this pull request to see the results displayed on the Hub leaderboard.
Evaluate your model on more datasets here.