Text Classification
Transformers
Safetensors
deberta-v2
stance-detection
cross-lingual
multilingual
mdeberta-v3
politics
trackio
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use MatteoFasulo/mdeberta-v3-xstance with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MatteoFasulo/mdeberta-v3-xstance with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MatteoFasulo/mdeberta-v3-xstance")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MatteoFasulo/mdeberta-v3-xstance") model = AutoModelForSequenceClassification.from_pretrained("MatteoFasulo/mdeberta-v3-xstance", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update mdeberta_finetuned.py
Verified signature64b269c -
Update README.md
Verified signature80610a8 -
Upload mdeberta-v3_pred.jsonl
Verified signaturea536c5f -
Update README.md
Verified signature20f92fa -
Create mdeberta_finetuned.py
Verified signature7735f01 -
Update README.md
Verified signature8911dbb -
End of training
Verified signature53f0a4b -
Upload DebertaV2ForSequenceClassification
Verified signature2c45e6e -
Upload tokenizer
Verified signaturef208fe7 -
Training in progress, epoch 3
Verified signaturedc1c2e9 -
Training in progress, epoch 2
Verified signatured7a384b -
Training in progress, epoch 1
Verified signatured91fa28 -
Training in progress, epoch 1
Verified signaturec949f9a -
initial commit
Verified signaturedbcff85