Text Classification
Transformers
Safetensors
deberta-v2
hierarchical-classification
climate-change
ukraine-russia-war
narrative-classification
multilingual
text-embeddings-inference
Instructions to use AWCO/mdeberta-v3-base-narratives-classifier-hierarchical with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AWCO/mdeberta-v3-base-narratives-classifier-hierarchical with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AWCO/mdeberta-v3-base-narratives-classifier-hierarchical")# Load model directly from transformers import AutoTokenizer, MultiHeadDebertaForHierarchicalClassification tokenizer = AutoTokenizer.from_pretrained("AWCO/mdeberta-v3-base-narratives-classifier-hierarchical") model = MultiHeadDebertaForHierarchicalClassification.from_pretrained("AWCO/mdeberta-v3-base-narratives-classifier-hierarchical") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a8be4185e71a5dd5a2c99bb7e2776908ccbc1d50aa841ec92e04aa9772e0ca6
- Size of remote file:
- 6.93 kB
- SHA256:
- 6d5c0b9c6cd244fefca1a4de7016f71ff09cdaffc96c539f915d2be933131e5a
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