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:
- a0a9085d5745e4f5fbfa89f1fb68f75d330bc6c328d0e4b67da1d130a4fa1e54
- Size of remote file:
- 498 MB
- SHA256:
- c85d7af9b6515196a8973506b382770c7a649778b05a517ed25d02388c4deea1
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