Instructions to use Maaz911/intent-distilbert-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Maaz911/intent-distilbert-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Maaz911/intent-distilbert-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Maaz911/intent-distilbert-classifier") model = AutoModelForSequenceClassification.from_pretrained("Maaz911/intent-distilbert-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b97ffa79138fc05f968b1511f92260326c6c9b3c62472725e6bac6de3b2465d
- Size of remote file:
- 536 MB
- SHA256:
- afdc8f0e1808173b785d01bcc201118b982e41827b326764d16035713e36781f
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