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:
- 9d96aee0f1d2d89cfe12b8e754b5ffec02266ffc91ae37577f933af8c95fc999
- Size of remote file:
- 5.43 kB
- SHA256:
- 3a4ef0949c63c4725f73e5907592dd46a48cd7a24f8eb1fddc1037ac650af53b
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