Instructions to use CatBarks/GPT2ES_ClassWeighted2_2bce_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CatBarks/GPT2ES_ClassWeighted2_2bce_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CatBarks/GPT2ES_ClassWeighted2_2bce_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CatBarks/GPT2ES_ClassWeighted2_2bce_model") model = AutoModelForSequenceClassification.from_pretrained("CatBarks/GPT2ES_ClassWeighted2_2bce_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 52c08a222fa052983d43f5c1ad577d28b0c0f0d985e9d891a55f11966f9c61ce
- Size of remote file:
- 498 MB
- SHA256:
- 28960858e70263aa5b1d66863e2565f8c858bb7da3b2e4b6e760997185bff77d
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