Instructions to use callgg/fastvlm-7b-bf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use callgg/fastvlm-7b-bf16 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-7b-bf16", 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:
- 878ef27b0c18ae21f9b6f2256533b07ffe6b5650fdaecb6754bce7d4fab60c7f
- Size of remote file:
- 6.58 kB
- SHA256:
- 2f8b8e614328387112b4f730cb632baf75812b6bde9137b83718752ecb690232
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