Instructions to use seduerr/sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seduerr/sentiment with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("seduerr/sentiment") model = AutoModelForSeq2SeqLM.from_pretrained("seduerr/sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c57372a41308f72b3df9ac0d554a3a4b22937acf676585dde45318fbccb49b93
- Size of remote file:
- 242 MB
- SHA256:
- d20585b7682ae75cca5f32438d6a86bd30134ae4d25c834b4454b4486639d4e2
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