Text Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use naylaarr/results-deberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use naylaarr/results-deberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="naylaarr/results-deberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("naylaarr/results-deberta") model = AutoModelForSequenceClassification.from_pretrained("naylaarr/results-deberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac516a5734a10e1a14a8adb78ef20e475723a86fb33c929cdc3f30678f7f0e5e
- Size of remote file:
- 5.24 kB
- SHA256:
- bc74b194a78e056cef55eea9fbe467be555c605e489d4043524b42f2664a4aa9
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