Instructions to use CatBarks/GPT2ES_ClassWeighted4_1bce_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CatBarks/GPT2ES_ClassWeighted4_1bce_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CatBarks/GPT2ES_ClassWeighted4_1bce_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CatBarks/GPT2ES_ClassWeighted4_1bce_model") model = AutoModelForSequenceClassification.from_pretrained("CatBarks/GPT2ES_ClassWeighted4_1bce_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f15b2bf672188ebf17c92d4c334253b49456e562aabbbad8dd719bdaf6b566b2
- Size of remote file:
- 498 MB
- SHA256:
- bb1be351a61dd9e46be300dbbaf2e1152f0dc4cfb9ed83ef6171bfa17c09aabd
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