Instructions to use warleygsantos/segmentation-observations with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use warleygsantos/segmentation-observations with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="warleygsantos/segmentation-observations")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("warleygsantos/segmentation-observations") model = AutoModelForSequenceClassification.from_pretrained("warleygsantos/segmentation-observations") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a8da72bd9447b486edcd7be02998338201e6cc9bd58be657dfad724017e6f999
- Size of remote file:
- 436 MB
- SHA256:
- 422767ccb0702a839603ace2085bf6932a3997425c8f741cf775f6d89c00de16
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