Text Classification
Transformers
TensorBoard
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use MohammadKarami/mdebertav3task1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MohammadKarami/mdebertav3task1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MohammadKarami/mdebertav3task1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MohammadKarami/mdebertav3task1") model = AutoModelForSequenceClassification.from_pretrained("MohammadKarami/mdebertav3task1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dc9091a88c97c25762f4b39ee58d82f0b4aa46a313886494ed392411fa3c467d
- Size of remote file:
- 16.3 MB
- SHA256:
- 5e26ec8cd2234df8edcc6e8c207b66b3162360f9fdc46ee4526a440d0d9d0bb9
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