Instructions to use CatBarks/bertES_ClassWeighted001_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CatBarks/bertES_ClassWeighted001_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CatBarks/bertES_ClassWeighted001_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CatBarks/bertES_ClassWeighted001_model") model = AutoModelForSequenceClassification.from_pretrained("CatBarks/bertES_ClassWeighted001_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7bb7215a08a405608d6eec17a825e5bb9971c8fc7ee6c31a56c78b3e73a6e443
- Size of remote file:
- 438 MB
- SHA256:
- 3239f4c7e09826788e743534b391a0ef4a81d1afdbd55c133ba32ec966a22140
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