imnotednamode
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Update README.md
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README.md
CHANGED
@@ -28,7 +28,7 @@ To use:
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from diffusers import MochiPipeline, MochiTransformer3DModel
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from diffusers.utils import export_to_video
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transformer = MochiTransformer3DModel.from_pretrained("imnotednamode/mochi-1-preview-mix-nf4-small", torch_dtype=torch.bfloat16)
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pipe = MochiPipeline.from_pretrained("mochi-1-
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pipe.enable_model_cpu_offload()
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pipe.enable_vae_tiling()
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frames = pipe("A camera follows a squirrel running around on a tree branch", num_inference_steps=100, guidance_scale=4.5, height=480, width=848, num_frames=161).frames[0]
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@@ -43,6 +43,6 @@ from diffusers import MochiPipeline, MochiTransformer3DModel, BitsAndBytesConfig
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import torch
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quantization_config = BitsAndBytesConfig(load_in_4bit=True, bnb_4bit_compute_dtype=torch.bfloat16, bnb_4bit_quant_type="nf4", llm_int8_skip_modules=["final_layer", "x_embedder.proj", "t_embedder", "pos_frequencies", "t5"])
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# Please convert mochi to diffusers first
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transformer = MochiTransformer3DModel.from_pretrained("mochi-1-
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transformer.save_pretrained("mochi-1-preview-nf4")
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```
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from diffusers import MochiPipeline, MochiTransformer3DModel
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from diffusers.utils import export_to_video
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transformer = MochiTransformer3DModel.from_pretrained("imnotednamode/mochi-1-preview-mix-nf4-small", torch_dtype=torch.bfloat16)
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pipe = MochiPipeline.from_pretrained("genmo/mochi-1-preview", torch_dtype=torch.bfloat16, transformer=transformer)
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pipe.enable_model_cpu_offload()
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pipe.enable_vae_tiling()
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frames = pipe("A camera follows a squirrel running around on a tree branch", num_inference_steps=100, guidance_scale=4.5, height=480, width=848, num_frames=161).frames[0]
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import torch
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quantization_config = BitsAndBytesConfig(load_in_4bit=True, bnb_4bit_compute_dtype=torch.bfloat16, bnb_4bit_quant_type="nf4", llm_int8_skip_modules=["final_layer", "x_embedder.proj", "t_embedder", "pos_frequencies", "t5"])
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# Please convert mochi to diffusers first
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transformer = MochiTransformer3DModel.from_pretrained("genmo/mochi-1-preview", variant="refs/pr/18", subfolder="transformer", quantization_config=quantization_config, torch_dtype=torch.bfloat16)
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transformer.save_pretrained("mochi-1-preview-nf4")
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```
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