Instructions to use Mantis-VL/mantis-8b-idefics2-classification-example_4096_regression with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mantis-VL/mantis-8b-idefics2-classification-example_4096_regression with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mantis-VL/mantis-8b-idefics2-classification-example_4096_regression")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("Mantis-VL/mantis-8b-idefics2-classification-example_4096_regression") model = AutoModelForSequenceClassification.from_pretrained("Mantis-VL/mantis-8b-idefics2-classification-example_4096_regression") - Notebooks
- Google Colab
- Kaggle
File size: 461 Bytes
cdfbb58 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | {
"do_convert_rgb": true,
"do_image_splitting": false,
"do_normalize": true,
"do_pad": true,
"do_rescale": true,
"do_resize": true,
"image_mean": [
0.5,
0.5,
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],
"image_processor_type": "Idefics2ImageProcessor",
"image_std": [
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],
"processor_class": "Idefics2Processor",
"resample": 2,
"rescale_factor": 0.00392156862745098,
"size": {
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}
}
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