Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use sambodhan/urgency_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sambodhan/urgency_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sambodhan/urgency_classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sambodhan/urgency_classifier") model = AutoModelForSequenceClassification.from_pretrained("sambodhan/urgency_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from sambodhan/urgency_classifier: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/sambodhan/urgency_classifier/resolve/main/tokenizer.json
- Command line
-
hf download hf://sambodhan/urgency_classifier/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/sambodhan/urgency_classifier/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 128e4bea076b1238bd45d07d4676afd1e6788fe105da8bcc2d0d8cb931b1700d
- Size of remote file:
- 17.1 MB
- SHA256:
- 8373f9cd3d27591e1924426bcc1c8799bc5a9affc4fc857982c5d66668dd1f41
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