Text Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use KingTechnician/deberta-v3-base_LOGIC_Native with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KingTechnician/deberta-v3-base_LOGIC_Native with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KingTechnician/deberta-v3-base_LOGIC_Native")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KingTechnician/deberta-v3-base_LOGIC_Native") model = AutoModelForSequenceClassification.from_pretrained("KingTechnician/deberta-v3-base_LOGIC_Native") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4a5e2936a31e52bd62b0510f5fe4600e36d0e14ecddee88cacd4334eabd2826b
- Size of remote file:
- 5.27 kB
- SHA256:
- 4d07f821a31392ccf897f5f986e0c5504b6ad2f99642981fa57b0b5349864547
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