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 training_args.bin from sambodhan/urgency_classifier: direct link, hf CLI and curl.
- Browser
- Download file 5.78 kB
-
https://huggingface.co/sambodhan/urgency_classifier/resolve/main/training_args.bin
- Command line
-
hf download hf://sambodhan/urgency_classifier/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/sambodhan/urgency_classifier/resolve/main/training_args.bin
5.78 kB
- Xet hash:
- 8bcf20d3d223a06ae99eb45a275524c9b9668cdd2a5b429ba62aa078aa364cb7
- Size of remote file:
- 5.78 kB
- SHA256:
- 9ba6b6f5ff2bd9ccf82f5a1b0e713463fcc57f3d68a838f48fd912447cd36c1d
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