Instructions to use CatBarks/GPT2ES_ClassWeighted1_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CatBarks/GPT2ES_ClassWeighted1_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CatBarks/GPT2ES_ClassWeighted1_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CatBarks/GPT2ES_ClassWeighted1_model") model = AutoModelForSequenceClassification.from_pretrained("CatBarks/GPT2ES_ClassWeighted1_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ecad483b8b04ac868b188a5d55f10fd794bd86a7fd429f9686b023d2046c8a35
- Size of remote file:
- 498 MB
- SHA256:
- 18ff23c42d330ecae17ac2fa8c51b163bfabb64eb8aaf32f3e8ea80db883e90d
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