Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Hwijung/distilbert-base-uncased-finetuned-clinc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hwijung/distilbert-base-uncased-finetuned-clinc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Hwijung/distilbert-base-uncased-finetuned-clinc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Hwijung/distilbert-base-uncased-finetuned-clinc") model = AutoModelForSequenceClassification.from_pretrained("Hwijung/distilbert-base-uncased-finetuned-clinc") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ce02c74f7f9708a4c720463d296bfaa0ca5ab5c00670e63b591edefe723f165b
- Size of remote file:
- 2.74 kB
- SHA256:
- f8676a0e3ea757edd213636f8499a177f1a72e24d7443bc2978863dd74527867
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