Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use KCourtney/distilbert-base-uncased-distilled-clinc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KCourtney/distilbert-base-uncased-distilled-clinc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KCourtney/distilbert-base-uncased-distilled-clinc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KCourtney/distilbert-base-uncased-distilled-clinc") model = AutoModelForSequenceClassification.from_pretrained("KCourtney/distilbert-base-uncased-distilled-clinc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a142a63b0227fd2f95cfa62c50ad21153554ff7d9565f9b4b4a2fe625a9afcd
- Size of remote file:
- 5.43 kB
- SHA256:
- fe9f7eac7fb9ec14901fa7ca1fd05ff89c4d9a747f988f336d929a3fe9a9db16
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