Instructions to use handraise-dev/492_Miro-Dove-3M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use handraise-dev/492_Miro-Dove-3M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="handraise-dev/492_Miro-Dove-3M")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("handraise-dev/492_Miro-Dove-3M") model = AutoModelForSequenceClassification.from_pretrained("handraise-dev/492_Miro-Dove-3M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2d5ac87dca6a1f2dcbded18b7fdc20ae05afdc9cb013123602a41d8e2e7c9406
- Size of remote file:
- 4.92 kB
- SHA256:
- c10ae44ed0b0330111546f0f8df7b8a3917010678ecc96f27cec92810d518e39
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