Instructions to use CatBarks/GPT2ES_ClassWeighted1_2bce_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CatBarks/GPT2ES_ClassWeighted1_2bce_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CatBarks/GPT2ES_ClassWeighted1_2bce_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CatBarks/GPT2ES_ClassWeighted1_2bce_model") model = AutoModelForSequenceClassification.from_pretrained("CatBarks/GPT2ES_ClassWeighted1_2bce_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9071b0729a0d9ec87e4e659e6a3fac830883af4b3d03c575b90aec179f8976bd
- Size of remote file:
- 498 MB
- SHA256:
- 18a73b76a3b245497597cd9bd7df706ec4a33bdc5d2bd60ccb53d5d070fac8d8
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