Text Classification
Transformers
ONNX
Safetensors
deberta-v2
claim-detection
claim-verification
deberta
Eval Results (legacy)
text-embeddings-inference
Instructions to use GLLhJpFfYB/claim-gate-mdeberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GLLhJpFfYB/claim-gate-mdeberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="GLLhJpFfYB/claim-gate-mdeberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("GLLhJpFfYB/claim-gate-mdeberta") model = AutoModelForSequenceClassification.from_pretrained("GLLhJpFfYB/claim-gate-mdeberta") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 04f57e9d9243f6495454a1298c6a1aee439d50e86ea6c5815ca7ffdd49e9900a
- Size of remote file:
- 16.4 MB
- SHA256:
- 35e2b7254bee739517e422891a9e0bfdd8a717b1826c8965e52a94e92be12544
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