Text Classification
Transformers
PyTorch
Safetensors
English
roberta
Eval Results (legacy)
text-embeddings-inference
Instructions to use AdamCodd/distilroberta-query-wellformedness with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AdamCodd/distilroberta-query-wellformedness with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AdamCodd/distilroberta-query-wellformedness")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AdamCodd/distilroberta-query-wellformedness") model = AutoModelForSequenceClassification.from_pretrained("AdamCodd/distilroberta-query-wellformedness", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2ec999e8b75708d356085c9618c9c2228f2a00ed6787d0537564049d654574ed
- Size of remote file:
- 329 MB
- SHA256:
- f6c3901b95c22771dd579d07fa8fbe5243535fd841473098d69b656264a82b81
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