Text Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use mhdafifan/mdeberta-fiqhqa-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mhdafifan/mdeberta-fiqhqa-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mhdafifan/mdeberta-fiqhqa-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mhdafifan/mdeberta-fiqhqa-classifier") model = AutoModelForSequenceClassification.from_pretrained("mhdafifan/mdeberta-fiqhqa-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 81b67ee4f01b4e5a7a03b8346f101ad1a71f53a1dc082cb0c7c27b036db7cb02
- Size of remote file:
- 16.4 MB
- SHA256:
- b98fa6759a0532a3223d7004f7a7906ba107d1a87d779bee9990d730d3a332ef
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