Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use kmcjeong/result with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kmcjeong/result with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kmcjeong/result")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kmcjeong/result") model = AutoModelForSequenceClassification.from_pretrained("kmcjeong/result") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 22b1328b4d81d5fc16db63d50477ab3fb11f922e1880b56ac51c5c30c4630dba
- Size of remote file:
- 499 MB
- SHA256:
- e295165a369f8f9ade3c0768cc231cbccbe710b7928944952c4b097382230dd0
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