Text Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use lopentu/microsoft-deberta-v3-base-DottedWSD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lopentu/microsoft-deberta-v3-base-DottedWSD with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lopentu/microsoft-deberta-v3-base-DottedWSD")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lopentu/microsoft-deberta-v3-base-DottedWSD") model = AutoModelForSequenceClassification.from_pretrained("lopentu/microsoft-deberta-v3-base-DottedWSD") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 725882ca6da616386afa1b0c180e33a6f3944fff87a9e851118cc0232bbee28d
- Size of remote file:
- 5.43 kB
- SHA256:
- a8aced0d4ca74ac980a3cc259fffb15a79f428346e9f3ef535d6b98302dac57c
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