Instructions to use CatBarks/GPT2ES_ClassWeighted4_4bce_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CatBarks/GPT2ES_ClassWeighted4_4bce_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CatBarks/GPT2ES_ClassWeighted4_4bce_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CatBarks/GPT2ES_ClassWeighted4_4bce_model") model = AutoModelForSequenceClassification.from_pretrained("CatBarks/GPT2ES_ClassWeighted4_4bce_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 72839ce80285121641cef2000ff5e96ee1801468512b14db72cfd417271ca8d3
- Size of remote file:
- 498 MB
- SHA256:
- bf84efd096dc3f505f4c34d2e1788b1956b25e82d5c605440e63811266a21037
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