Text Classification
Transformers
Safetensors
deberta-v2
single_label_classification
question-answering
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use saiteki-kai/QA-DeBERTa-v3-large-binary-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use saiteki-kai/QA-DeBERTa-v3-large-binary-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="saiteki-kai/QA-DeBERTa-v3-large-binary-2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("saiteki-kai/QA-DeBERTa-v3-large-binary-2") model = AutoModelForSequenceClassification.from_pretrained("saiteki-kai/QA-DeBERTa-v3-large-binary-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8623a2e707fd95ea7ad5e742ff3dd20e86284bd7db11469db832aafa81b92122
- Size of remote file:
- 5.91 kB
- SHA256:
- 7e724c685d8508525726c5cd8271b8c4cd3a05cd73272f12ce1963345112d69b
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