Text Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use KingTechnician/deberta-v3-base_LOGIC_LRTC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KingTechnician/deberta-v3-base_LOGIC_LRTC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KingTechnician/deberta-v3-base_LOGIC_LRTC")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KingTechnician/deberta-v3-base_LOGIC_LRTC") model = AutoModelForSequenceClassification.from_pretrained("KingTechnician/deberta-v3-base_LOGIC_LRTC") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 192f5eb9ef29b0ccedb8fec3dfab97a9806ec5cb651223e2e1eaa83c32c7e20f
- Size of remote file:
- 5.27 kB
- SHA256:
- a9c32698fb234a2a97820521c091986c974d39a026ccc7321409539b7b1807e4
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