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:
- b28a9c0dc76284ccf841d31f73848c030d1183dc7149935e677cf7892017421e
- Size of remote file:
- 5.18 kB
- SHA256:
- 71ff2317e229cdd8b4d7b7e9a5dde70857903be8700eae5343d1afae9230f3c3
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