Instructions to use CatBarks/GPT2ES_ClassWeighted01_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CatBarks/GPT2ES_ClassWeighted01_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CatBarks/GPT2ES_ClassWeighted01_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CatBarks/GPT2ES_ClassWeighted01_model") model = AutoModelForSequenceClassification.from_pretrained("CatBarks/GPT2ES_ClassWeighted01_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8bf5f2af1c32799bf421914dde554abbb40c2e97c4875dba1efe502dd11debf4
- Size of remote file:
- 498 MB
- SHA256:
- 05b4a86e9c944c37a222795c46564c6533387adc0237a7a5fdbe347993d8f0d3
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