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Hi folks,
Thanks for sharing this very interesting project!
I've been trying to run gradio demo in a docker container with cuda 12.6 and flash attention 2.8.3.
I'm getting a strange error:
/usr/local/lib/python3.10/dist-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers
warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning)
[CustomFluxPipeline] Loading FLUX Pipeline
Loading checkpoint shards: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 6.38it/s]
Loading pipeline components...: 86%|█████████████████████████████████████████████████████████████████████████████████████▋ | 6/7 [00:01<00:00, 3.86it/s]You set `add_prefix_space`. The tokenizer needs to be converted from the slow tokenizers
Loading pipeline components...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████| 7/7 [00:01<00:00, 4.82it/s]
[Quantization] Start freezing
[Quantization] Finished
Quantization time: 21.46683645248413
UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=None`.
Downloading: "https://github.com/elliottzheng/face-detection/releases/download/0.0.1/Resnet50_Final.pth" to /root/.cache/torch/hub/checkpoints/Resnet50_Final.pth
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 104M/104M [00:01<00:00, 92.2MB/s]
[FlorenceSAM] init on device cuda
Some weights of Florence2ForConditionalGeneration were not initialized from the model checkpoint at /models/checkpoints/Florence-2-large and are newly initialized: ['language_model.lm_head.weight']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
Checkpoint root does not exist.
Init new modulation adapter
[load_dit_lora] no condition lora
Traceback (most recent call last):
File "/app/run_gradio.py", line 88, in <module>
load_dit_lora(model, model.pipe, config, dtype, init_device, f"{ckpt_root}", is_training=False)
File "/app/src/flux/pipeline_tools.py", line 650, in load_dit_lora
assert is_training
AssertionError
The models are located in /models/checkpoint directory vs. ./checkpoints and the environment variables are updated accordingly. I cant see any other changes that could have triggered this. Any thoughts?
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