Instructions to use CatBarks/bertES_ClassWeighted01_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CatBarks/bertES_ClassWeighted01_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CatBarks/bertES_ClassWeighted01_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CatBarks/bertES_ClassWeighted01_model") model = AutoModelForSequenceClassification.from_pretrained("CatBarks/bertES_ClassWeighted01_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e1297efcaaf2fd7f466e538905c7156a7f817d03bb29b22b24fb8041f37fb1af
- Size of remote file:
- 438 MB
- SHA256:
- 3f9daa6d36b45efeab2734d1e85df4b4b84d8b5eaa3c39d85e15d1aa4b556f58
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