Text Classification
Transformers
PyTorch
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use ejschwartz/oo-method-test-model-bylibrary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ejschwartz/oo-method-test-model-bylibrary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ejschwartz/oo-method-test-model-bylibrary")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ejschwartz/oo-method-test-model-bylibrary") model = AutoModelForSequenceClassification.from_pretrained("ejschwartz/oo-method-test-model-bylibrary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6f99076e0e35c9a7182854467c2cfd0c2b6abb0f6cc4a1b072ce03cbd6516257
- Size of remote file:
- 334 MB
- SHA256:
- 725ddec0d55e9a1053b7194d01979d24baf6ea199b9a8bf7135f0ef95482bbc1
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