Text Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use tralon/test-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tralon/test-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tralon/test-1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tralon/test-1") model = AutoModelForSequenceClassification.from_pretrained("tralon/test-1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2590f7d3cb5f994e114c1fe6581ad795c93404cabe99c40a0b10de2bfd4b0184
- Size of remote file:
- 4.86 kB
- SHA256:
- 22df37287ac0ad82895f82d4b18c730c063576a5261e97eaa5486196607a59cd
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