Text Classification
Transformers
ONNX
Safetensors
English
roberta
Eval Results (legacy)
text-embeddings-inference
Instructions to use AdamCodd/distilroberta-NLI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AdamCodd/distilroberta-NLI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AdamCodd/distilroberta-NLI")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AdamCodd/distilroberta-NLI") model = AutoModelForSequenceClassification.from_pretrained("AdamCodd/distilroberta-NLI", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ee9a829913a133fc71464b1b4e3f8d9c20bdfe4a7a26e035657176c5397a6c64
- Size of remote file:
- 3.26 kB
- SHA256:
- 04f2e0baaa9dbdee7593f7f44df095e0085a14034489e9d7de6957550d638ac6
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