Instructions to use CatBarks/GPT2ES_ClassWeighted4_2bce_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CatBarks/GPT2ES_ClassWeighted4_2bce_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CatBarks/GPT2ES_ClassWeighted4_2bce_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CatBarks/GPT2ES_ClassWeighted4_2bce_model") model = AutoModelForSequenceClassification.from_pretrained("CatBarks/GPT2ES_ClassWeighted4_2bce_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a742eda6537edf5b1befe3b595b2d26727b1b2df3162850740fcf60ff0b91b76
- Size of remote file:
- 498 MB
- SHA256:
- a444c2147aea74ec0b62b6cf851c73b83ab98a202dc95edff6fcbfa0702ef49e
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