Text Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use MRAIRR/intent_classification_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MRAIRR/intent_classification_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MRAIRR/intent_classification_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MRAIRR/intent_classification_model") model = AutoModelForSequenceClassification.from_pretrained("MRAIRR/intent_classification_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e599765bbc60853056b4ae647dbf2234bdee3d6a6e59621e1f6bfa9a23817218
- Size of remote file:
- 541 MB
- SHA256:
- 064e5e287fe33bd4d8810d467442dc7b8ecf4b3a3300a994ee15531d85f77515
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