Text Classification
Transformers
PyTorch
Safetensors
English
distilbert
intent-detection
communication-analysis
multi-label-classification
psychology
nlp
Eval Results (legacy)
text-embeddings-inference
Instructions to use SamanthaStorm/intentanalyzer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SamanthaStorm/intentanalyzer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SamanthaStorm/intentanalyzer")# Load model directly from transformers import AutoTokenizer, MultiLabelIntentClassifier tokenizer = AutoTokenizer.from_pretrained("SamanthaStorm/intentanalyzer") model = MultiLabelIntentClassifier.from_pretrained("SamanthaStorm/intentanalyzer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 773a93239ea6c87f81b613e54876a1c871a357bc11900fcb0d1578c8245db449
- Size of remote file:
- 266 MB
- SHA256:
- 76ff6f53405352d5cdb384c2abb6e685d03cea834654311c19d79ec3984a7e66
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