Instructions to use lrei/distilroberta-base-emolit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lrei/distilroberta-base-emolit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lrei/distilroberta-base-emolit")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lrei/distilroberta-base-emolit") model = AutoModelForSequenceClassification.from_pretrained("lrei/distilroberta-base-emolit") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 69b996b49b06239555aabfb0aaf62313c47edd3fa761cabc5c5300f4a18319eb
- Size of remote file:
- 499 MB
- SHA256:
- d9183a055cc3328fb7f52ee9bc4a56fe3481d2812116ebe62e8094fe95e5f641
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