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
- Xet hash:
- db7e66a76272165696862fd0860820179e594f868e57e533c2891be825623490
- Size of remote file:
- 11.4 MB
- SHA256:
- 8bb55926dbf36523cd143a5805102a9a516df89f7010313d182e1e710d94fb15
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