NielsRogge
crach
transformer_4bit = FluxTransformer2DModel.from_pretrained(ckpt_4bit_id, subfolder="transformer") pipeline = FluxPipeline.from_pretrained( ckpt_id, text_encoder=None, text_encoder_2=None, tokenizer=None, tokenizer_2=None, transformer=transformer_4bit, torch_dtype=torch.float16, ) pipeline.enable_model_cpu_offload()
Your session crashed after using all available RAM.
in colab t4
from diffusers import FluxTransformer2DModel, FluxPipeline import torch model_id = "black-forest-labs/FLUX.1-dev" nf4_id = "sayakpaul/flux.1-dev-nf4-with-bnb-integration" model_nf4 = FluxTransformer2DModel.from_pretrained(nf4_id, torch_dtype=torch.bfloat16) print(model_nf4.dtype) print(model_nf4.config.quantization_config) pipe = FluxPipeline.from_pretrained(model_id, transformer=model_nf4, torch_dtype=torch.bfloat16) pipe.enable_model_cpu_offload() prompt = "car" image = pipe(prompt, guidance_scale=3.5, num_inference_steps=5, generator=torch.manual_seed(0)).images[0] image.save("flux-nf4-dev-loaded.png")
Your session crashed after using all available RAM
in colab t4
https://github.com/NielsRogge/Transformers-Tutorials/blob/master/Flux/Run_Flux_on_an_8GB_machine.ipynb?source=post_page-----7daa9fd88db5--------------------------------
