Instructions to use Greys/sentimentgrey with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Greys/sentimentgrey with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Greys/sentimentgrey")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Greys/sentimentgrey") model = AutoModel.from_pretrained("Greys/sentimentgrey", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c8216207a39fbe27fa89c2e1c2a56ba11f2138b751fc1187c65d7a83a0f9951a
- Size of remote file:
- 265 MB
- SHA256:
- 1df15ef6ca103a52df977eec51dd1058d5f6a2fdf5b3ae5d2e7fc225e9801143
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