Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use ashrielbrian/distilbert-base-uncased-finetuned-clinc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ashrielbrian/distilbert-base-uncased-finetuned-clinc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ashrielbrian/distilbert-base-uncased-finetuned-clinc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ashrielbrian/distilbert-base-uncased-finetuned-clinc") model = AutoModelForSequenceClassification.from_pretrained("ashrielbrian/distilbert-base-uncased-finetuned-clinc") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 753f6a81f1145efc998e2e9221bd3e735dbd79266ab065899cb130d99d900dc8
- Size of remote file:
- 268 MB
- SHA256:
- d79659f7cb37706ec51de1c9dee3202aa5c34e38ef7aa6cb759ed47b01ad2136
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