Text Classification
Transformers
PyTorch
Safetensors
English
roberta
banking
intent
multiclass
text-embeddings-inference
Instructions to use mrm8488/distilroberta-finetuned-banking77 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/distilroberta-finetuned-banking77 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mrm8488/distilroberta-finetuned-banking77")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mrm8488/distilroberta-finetuned-banking77") model = AutoModelForSequenceClassification.from_pretrained("mrm8488/distilroberta-finetuned-banking77") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b952c71f4991e4ec0f463d93c8ab107a9a223d90ac460e64f53931a8ea805ade
- Size of remote file:
- 329 MB
- SHA256:
- 1cfdb13af32c460c46e54fbd35917a8893378350d05ec62a695b79df389c5aee
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