Instructions to use CatBarks/GPT2ES_ClassWeighted1_4bce_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CatBarks/GPT2ES_ClassWeighted1_4bce_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CatBarks/GPT2ES_ClassWeighted1_4bce_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CatBarks/GPT2ES_ClassWeighted1_4bce_model") model = AutoModelForSequenceClassification.from_pretrained("CatBarks/GPT2ES_ClassWeighted1_4bce_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 72f2af09ee9822e580eb98d8b42d1fdc37d79f82f04f724fea51dbbdd0681d37
- Size of remote file:
- 498 MB
- SHA256:
- 8ca563d22b99c06247ffbc697b403368d47e6726ab0d7f18310a9bcb4ffdd288
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