storytold/FineTrainers-Conditioning
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Adapter weights can be loaded.

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This commit is contained in:
CrossProduct
2025-02-04 16:46:45 +00:00
parent ea3cd5c753
commit 28165e67d0
5 changed files with 41 additions and 8 deletions
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finetrainers/conditioning/inference_example.py
+2 -1
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@@ -5,7 +5,7 @@ from diffusers.utils import export_to_video
from diffusers.utils import testing_utils
testing_utils.enable_full_determinism()
transformer = LTXVideoTransformer3DModel.from_pretrained("/home/ubuntu/upstream/finetrainers/ltx-video/ltxv_strip/checkpoint-38000/transformer/",torch_dtype=torch.bfloat16).to("cuda")
#transformer = LTXVideoTransformer3DModel.from_pretrained("/home/ubuntu/upstream/finetrainers/ltx-video/ltxv_strip/checkpoint-38000/transformer/",torch_dtype=torch.bfloat16).to("cuda")
pipe = LTXPipeline.from_pretrained(
"Lightricks/LTX-Video", torch_dtype=torch.bfloat16,
# transformer=transformer
@@ -20,6 +20,7 @@ for seconds in range(3, 8):
num_frames = seconds * 24
result = pipe(
guidance_scale=0,
prompt=prompt,
width=768,
height=512,