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:
- 1da7ae0dba0bb6bbaeeaddc6d20b8c75358d254968f286dbbffc1286adb5e84e
- Size of remote file:
- 4.92 kB
- SHA256:
- 310fe130ab31d3927cd1d95775c57c484ddc264472c06c0e6bc7a5dcf17567bb
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