Instructions to use Azma-AI/deberta-base-multi-label-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Azma-AI/deberta-base-multi-label-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Azma-AI/deberta-base-multi-label-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Azma-AI/deberta-base-multi-label-classifier") model = AutoModelForSequenceClassification.from_pretrained("Azma-AI/deberta-base-multi-label-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download spm.model from Azma-AI/deberta-base-multi-label-classifier: direct link, hf CLI and curl.
- Browser
- Download file 2.46 MB
-
https://huggingface.co/Azma-AI/deberta-base-multi-label-classifier/resolve/main/spm.model
- Command line
-
hf download hf://Azma-AI/deberta-base-multi-label-classifier/spm.model
-
curl -L -o spm.model https://huggingface.co/Azma-AI/deberta-base-multi-label-classifier/resolve/main/spm.model
2.46 MB
- Xet hash:
- ceef70ee5c068f2e8ec2ea787d1566d2f5846b612f0e0a3879edffa246dc91cf
- Size of remote file:
- 2.46 MB
- SHA256:
- c679fbf93643d19aab7ee10c0b99e460bdbc02fedf34b92b05af343b4af586fd
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