Instructions to use callgg/fastvlm-caption with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use callgg/fastvlm-caption with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("callgg/fastvlm-caption", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
File size: 467 Bytes
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"height": 1024,
"width": 1024
},
"do_center_crop": true,
"do_convert_rgb": true,
"do_normalize": true,
"do_rescale": true,
"do_resize": true,
"image_mean": [
0.0,
0.0,
0.0
],
"image_processor_type": "CLIPImageProcessor",
"image_std": [
1.0,
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],
"processor_class": "LlavaProcessor",
"resample": 3,
"rescale_factor": 0.00392156862745098,
"size": {
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}
}
|