Text Classification
Transformers
PyTorch
Enawené-Nawé
roberta
Trained with AutoTrain
text-embeddings-inference
Instructions to use karalif/simple-test-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karalif/simple-test-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karalif/simple-test-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karalif/simple-test-model") model = AutoModelForSequenceClassification.from_pretrained("karalif/simple-test-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c72531c456f118274398e219f2a6b4574acb605076d41c65599aa5b1dd9c60c2
- Size of remote file:
- 2.38 MB
- SHA256:
- 3b625b84411d20a4237e1dcaf90c5878396d8c0814af8bf94bfd8cd8df7eb7d2
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