Flux gym hangs on "download flux-dev" step and appears to not be doing anything
What happened?
I installed Flux Gym with the Stability Matrix UI. I was able to run it and get things set up with my dataset, captions, etc. When I click Train, it gets stuck on the "download flux-dev" step
I clearly already have Flux-dev model and VAE in the required folders for flux gym, too, so I don't know why it's even trying to download anything.
Steps to reproduce
Install Flux Gym Launch Flux Gym in Stability Matrix Setup your LORA info and input images Click "Train" Look at console window messages
Relevant logs
e
model_names=['flux-dev', 'flux-schnell', 'bdsqlsz/flux1-dev2pro-single']
Running on local URL: http://127.0.0.1:7860
2024-11-24 15:51:53 INFO HTTP Request: GET _client.py:1038
http://127.0.0.1:7860/startup-even
ts "HTTP/1.1 200 OK"
INFO HTTP Request: HEAD _client.py:1038
http://127.0.0.1:7860/ "HTTP/1.1
200 OK"
To create a public link, set `share=True` in `launch()`.
current_account=None
max_train_epochs=16 num_images=18, num_repeats=10, total_steps=2880
gen_sh: network_dim:4, max_train_epochs=16, save_every_n_epochs=4, timestep_sampling=shift, guidance_scale=1, vram=20G, sample_prompts=, sample_every_n_steps=0
original_advanced_component_values = ['', False, False, False, '', '', False, '', False, False, '', '', '', '', '', '', '', '', '', False, '', '', '', '', False, False, '', '', False, False, '', False, False, False, False, '', False, False, '', False, False, False, False, False, False, '', '', '', '', '', '', '', '', '', '', '', '', False, '', '', False, '', '', '', '', '', False, '', '', '', '', '', '', '', '', False, '', '', '', '', False, '', '', '', '', '', '', '', '', '', '', '', '', False, False, '', False, False, '', False, '', '', '', '', False, '', False, '', '', '', False, False, '', '', '', '', '', '', '', '', False, False, False, False, '', '', False, '', False, False, '', '', '', '', '', False, '', '', '', '', False, False, False, False, '', '', '', '', '', False, False, False, False, '', False]
gen_sh: network_dim:4, max_train_epochs=16, save_every_n_epochs=4, timestep_sampling=shift, guidance_scale=1, vram=20G, sample_prompts=, sample_every_n_steps=0
original_advanced_component_values = ['', False, False, False, '', '', False, '', False, False, '', '', '', '', '', '', '', '', '', False, '', '', '', '', False, False, '', '', False, False, '', False, False, False, False, '', False, False, '', False, False, False, False, False, False, '', '', '', '', '', '', '', '', '', '', '', '', False, '', '', False, '', '', '', '', '', False, '', '', '', '', '', '', '', '', False, '', '', '', '', False, '', '', '', '', '', '', '', '', '', '', '', '', False, False, '', False, False, '', False, '', '', '', '', False, '', False, '', '', '', False, False, '', '', '', '', '', '', '', '', False, False, False, False, '', '', False, '', False, False, '', '', '', '', '', False, '', '', '', '', False, False, False, False, '', '', '', '', '', False, False, False, False, '', False]
gen_sh: network_dim:4, max_train_epochs=16, save_every_n_epochs=4, timestep_sampling=shift, guidance_scale=1, vram=20G, sample_prompts=v3tta, sample_every_n_steps=0
original_advanced_component_values = ['', False, False, False, '', '', False, '', False, False, '', '', '', '', '', '', '', '', '', False, '', '', '', '', False, False, '', '', False, False, '', False, False, False, False, '', False, False, '', False, False, False, False, False, False, '', '', '', '', '', '', '', '', '', '', '', '', False, '', '', False, '', '', '', '', '', False, '', '', '', '', '', '', '', '', False, '', '', '', '', False, '', '', '', '', '', '', '', '', '', '', '', '', False, False, '', False, False, '', False, '', '', '', '', False, '', False, '', '', '', False, False, '', '', '', '', '', '', '', '', False, False, False, False, '', '', False, '', False, False, '', '', '', '', '', False, '', '', '', '', False, False, False, False, '', '', '', '', '', False, False, False, False, '', False]
max_train_epochs=16 num_images=18, num_repeats=9, total_steps=2592
max_train_epochs=16 num_images=18, num_repeats=8, total_steps=2304
gen_sh: network_dim:4, max_train_epochs=16, save_every_n_epochs=4, timestep_sampling=shift, guidance_scale=1, vram=20G, sample_prompts=v3tta, sample_every_n_steps=0
original_advanced_component_values = ['', False, False, False, '', '', False, '', False, False, '', '', '', '', '', '', '', '', '', False, '', '', '', '', False, False, '', '', False, False, '', False, False, False, False, '', False, False, '', False, False, False, False, False, False, '', '', '', '', '', '', '', '', '', '', '', '', False, '', '', False, '', '', '', '', '', False, '', '', '', '', '', '', '', '', False, '', '', '', '', False, '', '', '', '', '', '', '', '', '', '', '', '', False, False, '', False, False, '', False, '', '', '', '', False, '', False, '', '', '', False, False, '', '', '', '', '', '', '', '', False, False, False, False, '', '', False, '', False, False, '', '', '', '', '', False, '', '', '', '', False, False, False, False, '', '', '', '', '', False, False, False, False, '', False]
max_train_epochs=17 num_images=18, num_repeats=8, total_steps=2448
max_train_epochs=18 num_images=18, num_repeats=8, total_steps=2592
gen_sh: network_dim:4, max_train_epochs=18, save_every_n_epochs=4, timestep_sampling=shift, guidance_scale=1, vram=20G, sample_prompts=v3tta, sample_every_n_steps=0
original_advanced_component_values = ['', False, False, False, '', '', False, '', False, False, '', '', '', '', '', '', '', '', '', False, '', '', '', '', False, False, '', '', False, False, '', False, False, False, False, '', False, False, '', False, False, False, False, False, False, '', '', '', '', '', '', '', '', '', '', '', '', False, '', '', False, '', '', '', '', '', False, '', '', '', '', '', '', '', '', False, '', '', '', '', False, '', '', '', '', '', '', '', '', '', '', '', '', False, False, '', False, False, '', False, '', '', '', '', False, '', False, '', '', '', False, False, '', '', '', '', '', '', '', '', False, False, False, False, '', '', False, '', False, False, '', '', '', '', '', False, '', '', '', '', False, False, False, False, '', '', '', '', '', False, False, False, False, '', False]
gen_sh: network_dim:4, max_train_epochs=18, save_every_n_epochs=4, timestep_sampling=shift, guidance_scale=1, vram=20G, sample_prompts=v3tta, sample_every_n_steps=400
original_advanced_component_values = ['', False, False, False, '', '', False, '', False, False, '', '', '', '', '', '', '', '', '', False, '', '', '', '', False, False, '', '', False, False, '', False, False, False, False, '', False, False, '', False, False, False, False, False, False, '', '', '', '', '', '', '', '', '', '', '', '', False, '', '', False, '', '', '', '', '', False, '', '', '', '', '', '', '', '', False, '', '', '', '', False, '', '', '', '', '', '', '', '', '', '', '', '', False, False, '', False, False, '', False, '', '', '', '', False, '', False, '', '', '', False, False, '', '', '', '', '', '', '', '', False, False, False, False, '', '', False, '', False, False, '', '', '', '', '', False, '', '', '', '', False, False, False, False, '', '', '', '', '', False, False, False, False, '', False]
gen_sh: network_dim:4, max_train_epochs=18, save_every_n_epochs=4, timestep_sampling=shift, guidance_scale=1, vram=20G, sample_prompts=v3tta, sample_every_n_steps=400
original_advanced_component_values = ['', False, False, False, '', '', False, '', False, False, '', '', '', '', '', '', '', '', '', False, '', '', '', '', False, False, '', '', False, False, '', False, False, False, False, '', False, False, '', False, False, False, False, False, False, '', '', '', '', '', '', '', '', '', '', '', '', False, '', '', False, '', '', '', '', '', False, '', '', '', '', '', '', '', '', False, '', '', '', '', False, '', '', '', '', '', '', '', '', '', '', '', '', False, False, '', False, False, '', False, '', '', '', '', False, '', False, '', '', '', False, False, '', '', '', '', '', '', '', '', False, False, False, False, '', '', False, '', False, False, '', '', '', '', '', False, '', '', '', '', False, False, False, False, '', '', '', '', '', False, False, False, False, '', False]
current_account=None
gen_sh: network_dim:4, max_train_epochs=16, save_every_n_epochs=4, timestep_sampling=shift, guidance_scale=1, vram=20G, sample_prompts=, sample_every_n_steps=0
original_advanced_component_values = ['', False, False, False, '', '', False, '', False, False, '', '', '', '', '', '', '', '', '', False, '', '', '', '', False, False, '', '', False, False, '', False, False, False, False, '', False, False, '', False, False, False, False, False, False, '', '', '', '', '', '', '', '', '', '', '', '', False, '', '', False, '', '', '', '', '', False, '', '', '', '', '', '', '', '', False, '', '', '', '', False, '', '', '', '', '', '', '', '', '', '', '', '', False, False, '', False, False, '', False, '', '', '', '', False, '', False, '', '', '', False, False, '', '', '', '', '', '', '', '', False, False, False, False, '', '', False, '', False, False, '', '', '', '', '', False, '', '', '', '', False, False, False, False, '', '', '', '', '', False, False, False, False, '', False]
gen_sh: network_dim:4, max_train_epochs=16, save_every_n_epochs=4, timestep_sampling=shift, guidance_scale=1, vram=20G, sample_prompts=v3tta, sample_every_n_steps=0
original_advanced_component_values = ['', False, False, False, '', '', False, '', False, False, '', '', '', '', '', '', '', '', '', False, '', '', '', '', False, False, '', '', False, False, '', False, False, False, False, '', False, False, '', False, False, False, False, False, False, '', '', '', '', '', '', '', '', '', '', '', '', False, '', '', False, '', '', '', '', '', False, '', '', '', '', '', '', '', '', False, '', '', '', '', False, '', '', '', '', '', '', '', '', '', '', '', '', False, False, '', False, False, '', False, '', '', '', '', False, '', False, '', '', '', False, False, '', '', '', '', '', '', '', '', False, False, False, False, '', '', False, '', False, False, '', '', '', '', '', False, '', '', '', '', False, False, False, False, '', '', '', '', '', False, False, False, False, '', False]
gen_sh: network_dim:4, max_train_epochs=16, save_every_n_epochs=4, timestep_sampling=shift, guidance_scale=1, vram=16G, sample_prompts=v3tta, sample_every_n_steps=0
original_advanced_component_values = ['', False, False, False, '', '', False, '', False, False, '', '', '', '', '', '', '', '', '', False, '', '', '', '', False, False, '', '', False, False, '', False, False, False, False, '', False, False, '', False, False, False, False, False, False, '', '', '', '', '', '', '', '', '', '', '', '', False, '', '', False, '', '', '', '', '', False, '', '', '', '', '', '', '', '', False, '', '', '', '', False, '', '', '', '', '', '', '', '', '', '', '', '', False, False, '', False, False, '', False, '', '', '', '', False, '', False, '', '', '', False, False, '', '', '', '', '', '', '', '', False, False, False, False, '', '', False, '', False, False, '', '', '', '', '', False, '', '', '', '', False, False, False, False, '', '', '', '', '', False, False, False, False, '', False]
gen_sh: network_dim:4, max_train_epochs=16, save_every_n_epochs=4, timestep_sampling=shift, guidance_scale=1, vram=16G, sample_prompts=v3tta, sample_every_n_steps=0
original_advanced_component_values = ['', False, False, False, '', '', False, '', False, False, '', '', '', '', '', '', '', '', '', False, '', '', '', '', False, False, '', '', False, False, '', False, False, False, False, '', False, False, '', False, False, False, False, False, False, '', '', '', '', '', '', '', '', '', '', '', '', False, '', '', False, '', '', '', '', '', False, '', '', '', '', '', '', '', '', False, '', '', '', '', False, '', '', '', '', '', '', '', '', '', '', '', '', False, False, '', False, False, '', False, '', '', '', '', False, '', False, '', '', '', False, False, '', '', '', '', '', '', '', '', False, False, False, False, '', '', False, '', False, False, '', '', '', '', '', False, '', '', '', '', False, False, False, False, '', '', '', '', '', False, False, False, False, '', False]
gen_sh: network_dim:4, max_train_epochs=18, save_every_n_epochs=4, timestep_sampling=shift, guidance_scale=1, vram=16G, sample_prompts=v3tta, sample_every_n_steps=0
original_advanced_component_values = ['', False, False, False, '', '', False, '', False, False, '', '', '', '', '', '', '', '', '', False, '', '', '', '', False, False, '', '', False, False, '', False, False, False, False, '', False, False, '', False, False, False, False, False, False, '', '', '', '', '', '', '', '', '', '', '', '', False, '', '', False, '', '', '', '', '', False, '', '', '', '', '', '', '', '', False, '', '', '', '', False, '', '', '', '', '', '', '', '', '', '', '', '', False, False, '', False, False, '', False, '', '', '', '', False, '', False, '', '', '', False, False, '', '', '', '', '', '', '', '', False, False, False, False, '', '', False, '', False, False, '', '', '', '', '', False, '', '', '', '', False, False, False, False, '', '', '', '', '', False, False, False, False, '', False]
max_train_epochs=18 num_images=18, num_repeats=8, total_steps=2592
gen_sh: network_dim:4, max_train_epochs=18, save_every_n_epochs=4, timestep_sampling=shift, guidance_scale=1, vram=16G, sample_prompts=v3tta, sample_every_n_steps=0
original_advanced_component_values = ['', False, False, False, '', '', False, '', False, False, '', '', '', '', '', '', '', '', '', False, '', '', '', '', False, False, '', '', False, False, '', False, False, False, False, '', False, False, '', False, False, False, False, False, False, '', '', '', '', '', '', '', '', '', '', '', '', False, '', '', False, '', '', '', '', '', False, '', '', '', '', '', '', '', '', False, '', '', '', '', False, '', '', '', '', '', '', '', '', '', '', '', '', False, False, '', False, False, '', False, '', '', '', '', False, '', False, '', '', '', False, False, '', '', '', '', '', '', '', '', False, False, False, False, '', '', False, '', False, False, '', '', '', '', '', False, '', '', '', '', False, False, False, False, '', '', '', '', '', False, False, False, False, '', False]
gen_sh: network_dim:4, max_train_epochs=18, save_every_n_epochs=4, timestep_sampling=shift, guidance_scale=1, vram=16G, sample_prompts=v3tta, sample_every_n_steps=400
original_advanced_component_values = ['', False, False, False, '', '', False, '', False, False, '', '', '', '', '', '', '', '', '', False, '', '', '', '', False, False, '', '', False, False, '', False, False, False, False, '', False, False, '', False, False, False, False, False, False, '', '', '', '', '', '', '', '', '', '', '', '', False, '', '', False, '', '', '', '', '', False, '', '', '', '', '', '', '', '', False, '', '', '', '', False, '', '', '', '', '', '', '', '', '', '', '', '', False, False, '', False, False, '', False, '', '', '', '', False, '', False, '', '', '', False, False, '', '', '', '', '', '', '', '', False, False, False, False, '', '', False, '', False, False, '', '', '', '', '', False, '', '', '', '', False, False, False, False, '', '', '', '', '', False, False, False, False, '', False]
gen_sh: network_dim:4, max_train_epochs=18, save_every_n_epochs=4, timestep_sampling=shift, guidance_scale=1, vram=16G, sample_prompts=v3tta, sample_every_n_steps=400
original_advanced_component_values = ['', False, False, False, '', '', False, '', False, False, '', '', '', '', '', '', '', '', '', False, '', '', '', '', False, False, '', '', False, False, '', False, False, False, False, '', False, False, '', False, False, False, False, False, False, '', '', '', '', '', '', '', '', '', '', '', '', False, '', '', False, '', '', '', '', '', False, '', '', '', '', '', '', '', '', False, '', '', '', '', False, '', '', '', '', '', '', '', '', '', '', '', '', False, False, '', False, False, '', False, '', '', '', '', False, '', False, '', '', '', False, False, '', '', '', '', '', '', '', '', False, False, False, False, '', '', False, '', False, False, '', '', '', '', '', False, '', '', '', '', False, False, False, False, '', '', '', '', '', False, False, False, False, '', False]
Creating dataset
resize datasets/corvette\20140410_150925.jpg : 1024x1364
image_path=datasets/corvette\20140410_150925.jpg, caption_path = C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\20140410_150925.txt, original_caption=v3tta
C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\20140410_150925.txt already exists. use the existing .txt file
resize datasets/corvette\20180423_230145.jpg : 1024x1259
image_path=datasets/corvette\20180423_230145.jpg, caption_path = C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\20180423_230145.txt, original_caption=v3tta
C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\20180423_230145.txt already exists. use the existing .txt file
resize datasets/corvette\20180425_120740.jpg : 1024x1364
image_path=datasets/corvette\20180425_120740.jpg, caption_path = C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\20180425_120740.txt, original_caption=v3tta
C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\20180425_120740.txt already exists. use the existing .txt file
resize datasets/corvette\20210405_091437.jpg : 1024x1364
image_path=datasets/corvette\20210405_091437.jpg, caption_path = C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\20210405_091437.txt, original_caption=v3tta
C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\20210405_091437.txt already exists. use the existing .txt file
resize datasets/corvette\AirBrush_20220711210322.jpg : 1024x1364
image_path=datasets/corvette\AirBrush_20220711210322.jpg, caption_path = C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\AirBrush_20220711210322.txt, original_caption=v3tta
C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\AirBrush_20220711210322.txt already exists. use the existing .txt file
resize datasets/corvette\IMG_20210606_122928124_BURST000_COVER_TOP.jpg : 1024x1364
image_path=datasets/corvette\IMG_20210606_122928124_BURST000_COVER_TOP.jpg, caption_path = C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\IMG_20210606_122928124_BURST000_COVER_TOP.txt, original_caption=v3tta
C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\IMG_20210606_122928124_BURST000_COVER_TOP.txt already exists. use the existing .txt file
resize datasets/corvette\IMG_20210610_091736587.jpg : 1024x1364
image_path=datasets/corvette\IMG_20210610_091736587.jpg, caption_path = C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\IMG_20210610_091736587.txt, original_caption=v3tta
C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\IMG_20210610_091736587.txt already exists. use the existing .txt file
resize datasets/corvette\IMG_20210610_091835714.jpg : 1024x1364
image_path=datasets/corvette\IMG_20210610_091835714.jpg, caption_path = C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\IMG_20210610_091835714.txt, original_caption=v3tta
C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\IMG_20210610_091835714.txt already exists. use the existing .txt file
resize datasets/corvette\IMG_20211010_165910716.jpg : 1024x1364
image_path=datasets/corvette\IMG_20211010_165910716.jpg, caption_path = C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\IMG_20211010_165910716.txt, original_caption=v3tta
C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\IMG_20211010_165910716.txt already exists. use the existing .txt file
resize datasets/corvette\IMG_20220225_114710509.jpg : 1024x1364
image_path=datasets/corvette\IMG_20220225_114710509.jpg, caption_path = C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\IMG_20220225_114710509.txt, original_caption=v3tta
C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\IMG_20220225_114710509.txt already exists. use the existing .txt file
resize datasets/corvette\IMG_20220311_093614531.jpg : 1024x1364
image_path=datasets/corvette\IMG_20220311_093614531.jpg, caption_path = C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\IMG_20220311_093614531.txt, original_caption=v3tta
C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\IMG_20220311_093614531.txt already exists. use the existing .txt file
resize datasets/corvette\IMG_20230528_101119964_HDR.jpg : 1024x1819
image_path=datasets/corvette\IMG_20230528_101119964_HDR.jpg, caption_path = C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\IMG_20230528_101119964_HDR.txt, original_caption=v3tta
C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\IMG_20230528_101119964_HDR.txt already exists. use the existing .txt file
resize datasets/corvette\IMG_20230705_144628420_MF_PORTRAIT.jpg : 1024x1360
image_path=datasets/corvette\IMG_20230705_144628420_MF_PORTRAIT.jpg, caption_path = C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\IMG_20230705_144628420_MF_PORTRAIT.txt, original_caption=v3tta
C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\IMG_20230705_144628420_MF_PORTRAIT.txt already exists. use the existing .txt file
resize datasets/corvette\IMG_20230705_144714376_MF_PORTRAIT.jpg : 1024x1360
image_path=datasets/corvette\IMG_20230705_144714376_MF_PORTRAIT.jpg, caption_path = C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\IMG_20230705_144714376_MF_PORTRAIT.txt, original_caption=v3tta
C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\IMG_20230705_144714376_MF_PORTRAIT.txt already exists. use the existing .txt file
resize datasets/corvette\IMG_20240207_094429697_HDR.jpg : 1024x1819
image_path=datasets/corvette\IMG_20240207_094429697_HDR.jpg, caption_path = C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\IMG_20240207_094429697_HDR.txt, original_caption=v3tta
C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\IMG_20240207_094429697_HDR.txt already exists. use the existing .txt file
resize datasets/corvette\IMG_20240207_094438057_HDR.jpg : 1024x1819
image_path=datasets/corvette\IMG_20240207_094438057_HDR.jpg, caption_path = C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\IMG_20240207_094438057_HDR.txt, original_caption=v3tta
C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\IMG_20240207_094438057_HDR.txt already exists. use the existing .txt file
resize datasets/corvette\original_88bcca8c-53d9-41f9-846c-5649ffef555c_IMG_20220125_164939884.jpg : 1055x1024
image_path=datasets/corvette\original_88bcca8c-53d9-41f9-846c-5649ffef555c_IMG_20220125_164939884.jpg, caption_path = C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\original_88bcca8c-53d9-41f9-846c-5649ffef555c_IMG_20220125_164939884.txt, original_caption=v3tta
C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\original_88bcca8c-53d9-41f9-846c-5649ffef555c_IMG_20220125_164939884.txt already exists. use the existing .txt file
resize datasets/corvette\Snapchat-710928474.jpg : 1024x1819
image_path=datasets/corvette\Snapchat-710928474.jpg, caption_path = C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\Snapchat-710928474.txt, original_caption=v3tta
C:\StabilityMatrix\AllData\Packages\FluxGym\datasets\corvette\Snapchat-710928474.txt already exists. use the existing .txt file
destination_folder datasets/corvette
download flux-dev
Version
2.12.3
What Operating System are you using?
Windows
I have precisely the same issue.
Hey there, Enter the folder where Fluxgym is located. Open the models.yaml file in a text editor and save the extension in the line that says flux1-dev.sft by typing .safetensor instead of .sft. Fluxgym will now work.
I have a similar issue, I would like to modify the file path so that Fluxgym does not need to download the file each time, but instead could locate the file on my computer. Do I need to delete the repo, base, and license from the code?
flux-dev: repo: cocktailpeanut/xulf-dev base: black-forest-labs/FLUX.1-dev license: other license_name: flux-1-dev-non-commercial-license license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md file: flux1-dev.sft (or: C:fluxgym\models\unet.cache\huggingface\download)
thanks!
Hey there, Enter the folder where Fluxgym is located. Open the models.yaml file in a text editor and save the extension in the line that says flux1-dev.sft by typing .safetensor instead of .sft. Fluxgym will now work.
Didn't work for me this way, but if you have flux1-dev.safetensor installed in the unet folder, you can rename it as .sft; and same for the vae. I tried this and it works just fine now
Hey there, Enter the folder where Fluxgym is located. Open the models.yaml file in a text editor and save the extension in the line that says flux1-dev.sft by typing .safetensor instead of .sft. Fluxgym will now work.
Didn't work for me this way, but if you have flux1-dev.safetensor installed in the unet folder, you can rename it as .sft; and same for the vae. I tried this and it works just fine now
This solved the issue for me. thank you