Sumit Mamoria sumitmamoria
sumitmamoria
/ inference_with_torchao_serialized.py
Created
August 22, 2024 04:22
— forked from sayakpaul/inference_with_torchao_serialized.py
Shows how to run Flux schnell under 17GBs without bells and whistles. It additionally shows how to serialize the quantized checkpoint and load it back.
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| import torch | |
| from huggingface_hub import hf_hub_download | |
| from diffusers import FluxTransformer2DModel, DiffusionPipeline | |
| dtype, device = torch.bfloat16, "cuda" | |
| ckpt_id = "black-forest-labs/FLUX.1-schnell" | |
| with torch.device("meta"): | |
| config = FluxTransformer2DModel.load_config(ckpt_id, subfolder="transformer") | |
| model = FluxTransformer2DModel.from_config(config).to(dtype) |