Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use wlg1/bcb_cost_roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wlg1/bcb_cost_roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wlg1/bcb_cost_roberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wlg1/bcb_cost_roberta") model = AutoModelForSequenceClassification.from_pretrained("wlg1/bcb_cost_roberta") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 94e09d77c5265ba2b4d83b28dcf340504d5f7e4e01b7a154879efb861c4c7bfa
- Size of remote file:
- 5.78 kB
- SHA256:
- 6ecf683dfaeff290e01ec43a7e5671cac268d9dc943fa86a6175c791df93de19
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