Instructions to use CatBarks/bertES_ClassWeighted100_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CatBarks/bertES_ClassWeighted100_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CatBarks/bertES_ClassWeighted100_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CatBarks/bertES_ClassWeighted100_model") model = AutoModelForSequenceClassification.from_pretrained("CatBarks/bertES_ClassWeighted100_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ee791d860a147ce714de7db7602b6383ff4c8536cdd004d9c126ebd3a6b2e4e2
- Size of remote file:
- 438 MB
- SHA256:
- fb71171f3d16073b522b3a1c516474a9236f05b7786955f63a700487316600ec
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