Instructions to use LogischeIP/SentimentT2_GPT2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LogischeIP/SentimentT2_GPT2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LogischeIP/SentimentT2_GPT2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LogischeIP/SentimentT2_GPT2") model = AutoModelForSequenceClassification.from_pretrained("LogischeIP/SentimentT2_GPT2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3f2967e5a2c5b8392300784d9f8046aa83f2ddf737ab15c8b7f4c74fc7e3c99f
- Size of remote file:
- 498 MB
- SHA256:
- e26ef8998b3af60784b5e86969675377cd913d59fe21c1c652c68304befc30a0
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