Instructions to use Maldak123/TOTVS_Churn_Risk_V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Maldak123/TOTVS_Churn_Risk_V2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Maldak123/TOTVS_Churn_Risk_V2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Maldak123/TOTVS_Churn_Risk_V2") model = AutoModelForSequenceClassification.from_pretrained("Maldak123/TOTVS_Churn_Risk_V2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4f49f37d63e5dff4b2517a4c9be9c688a5a7a7daf794d05715e145677233107b
- Size of remote file:
- 5.2 kB
- SHA256:
- 5516f5851d11085894670444e1d3d95d8d116beaab9e5041ce53b2c28e547b1a
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