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How do you use this model locally, similarly to using `llama-server -m <model>`? (I mean: outside direct or substantial use of Python, and running the Neural N
by mdp2021 13d ago
How do you use this model locally, similarly to using `llama-server -m <model>`?
(I mean: outside direct or substantial use of Python, and running the Neural Network in the most efficient way.)
- embedding-shape 13d agoProbably ComfyUI is one of the easiest way to get started with local image/video models. Or perhaps vLLM, if they have support for it already, would be something like `vllm serve <model> --omni --port 9080`
- utopiah 13d agowhy not just as you suggested i.e. https://qwen.readthedocs.io/en/latest/run_locally/llama.cpp.html#llama-server https://qwen.readthedocs.io/en/latest/run_locally/llama.cpp.... then get the result either via a UI or wget/curl it back?
- mdp2021 13d agoI am not sure that llama.cpp also supports image generation models.
- utopiah 13d agoit's multimodal, see https://github.com/ggml-org/llama.cpp/blob/master/docs/multimodal.md https://github.com/ggml-org/llama.cpp/blob/master/docs/multi...
- exe34 13d agoMultimodal doesn't guarantee input and output. > Currently, we support image, audio and video input.
- utopiah 13d agoSeems I'm missing something. Does this model support other inputs? Image outputs are supported, videos I'm not sure but I don't think that's an output, just a preview of the equirectangular example, so, same question here, what does this model outputs that isn't supported?
- deleted 13d ago[deleted]
- exe34 13d agoIt's a diffusion model, completely different from autoregressive attention models.
- utopiah 13d agolike https://github.com/ggml-org/llama.cpp/tree/master/examples/diffusion https://github.com/ggml-org/llama.cpp/tree/master/examples/d... ? At the risk of stating the obvious llama.cpp isn't just about LLaMa as https://github.com/ggml-org/llama.cpp/blob/master/src/llama-arch.h#L13 https://github.com/ggml-org/llama.cpp/blob/master/src/llama-... someone else pointed out.
- mdp2021 13d agoNot all architectures are supported by llama.cpp . The GGUF format encodes the NN in a standardized way, but then you need code that can use that NN structure. I understand that llama.cpp could only output text, last time I checked (I do not know how to find a good source for that though). See https://github.com/ggml-org/llama.cpp/blob/master/src/llama-arch.h https://github.com/ggml-org/llama.cpp/blob/master/src/llama-... , the enum llm_arch { ...
- fp64 13d agoon the linked GitHub page they list support Diffusers, ComfyUI, vLLM-Omni, SGLang, and LightX2V with links to each
- mdp2021 13d ago> Diffusers, ComfyUI, vLLM-Omni, SGLang, and LightX2V I think that's all Python (not a direct executable). You could just do (see the "Quick Start") four `pip install` and have a dozen lines script to generate the image. But `llama.cpp` and similar do not require e.g. installing Torch (or PyTorch) - you can use `llama.cpp` on a non-specialized machine.
- wgd 13d ago"just" I don't think I have ever once run "pip install transformers" and had it work without three rounds of fiddling
- mdp2021 13d agoOr trying to install the whole of CUDA on machines that do not even have a GPU (not Nvidia, not anything past the embedded)... Yep, that's (also) what I meant ;) Lean, efficient... Also sensible and trouble-less.
- iugtmkbdfil834 13d agoThe 'not nvidia' is no longer a deal breaker by itself.
- Iolaum 13d agoThere is difussion.cpp which is intended for those types of models. I set up krea-2-turbo with the help of ChatGPT 2 months ago, if you have a capable computer that's what I would suggest once it becomes supported.
- rwmj 13d agoAdditional question is what kind of local hardware would be required for this? 7B parameters sounds very light weight, but I'm not sure. (Edit: The download is 33 GB). Edit x2: As usual I'm in a twisty maze of pip packages that don't work together, with obscure errors about missing modules, even though I followed the instructions on the page to the letter. I really wish people didn't use Python for this stuff. A simple C/C++ program would be so much better.
- peri-cl 13d agoIt's about 16 GiB at Q8 quants (combining both the image and language parts). (Meaning, community quantized models from HuggingFace). I think it will technically run on anything that has enough memory. I just tried it on a standard laptop (dual-channel DDR5), and it took about 3 minutes for a 512x512. If you'd want to run it at interactive speeds, you would want a GPU (one which fits this in VRAM). > "I really wish people didn't use Python for this stuff. A simple C/C++ program would be so much better." You mean besides stable-diffusion.cpp ?
- rwmj 13d ago> You mean besides stable-diffusion.cpp ? Yes, thanks, I didn't know about that. Will try it.
- deleted 13d ago[deleted]
- nkhgfugjk 13d agoI am using sd.cpp, which is the cousin of llama.cpp: https://github.com/leejet/stable-diffusion.cpp https://github.com/leejet/stable-diffusion.cpp it already has day-0 qwen image 2.1 support!
- peri-cl 13d agoI've set it up on my local machine just now, as my first local image diffuser. I can confirm it's very easy. I tried stable-diffusion.cpp, following its compile guide here[0], and its Qwen Image-2.1 specific instructions here[1]. It works out of the box. I made a test pelican[2]. It took 3 minutes on a CPU. [0] https://github.com/leejet/stable-diffusion.cpp/blob/master/docs/build.md https://github.com/leejet/stable-diffusion.cpp/blob/master/d... [1] https://github.com/leejet/stable-diffusion.cpp/blob/master/docs/qwen_image_2.1.md https://github.com/leejet/stable-diffusion.cpp/blob/master/d... [2] https://i.ibb.co/yMknC2K/output.png https://i.ibb.co/yMknC2K/output.png
- mdp2021 13d agoThank you! Can you please check how much RAM does it consume (and require)?
- peri-cl 13d agoThis is what the runtime reports, at Q8: total params memory size = 15645.19MB (VRAM 15645.19MB, RAM 0.00MB): text_encoders 7669.77MB(VRAM), diffusion_model 7331.05MB(VRAM), vae 644.38MB(VRAM), controlnet 0.00MB(N/A), extensions 0.00MB(N/A)
- mdp2021 13d agoThat suggests that 16GB RAM will not be enough. In fact, like it appears in the reports above, it is "7b" as in > 7B parameters in its visual generation component It seems they calibrated the size to fill a 16GB VRAM near the limit. RAM requirements will vary.
- leumon 13d agoUnsloth Desktop is the easiest way imo. There are already gguf quants of this model, or simply wait until the official one comes out.
- finnjohnsen2 13d agoI use opencode + <a decent saas llm> to set up all this new ai generation stuff. GLM-5.3 is my current gun. Safely inside podman containers too because I dont trust this fast moving python eco system at all. Never do I want this running on my main OS. I have FLUX.2 klein and dev, Ideogram, LaDA-Image and SenseNova locally. Works great. Ive never touched a file. The days of making container yamls myself is over. I read them but I dont edit anymore.
- iugtmkbdfil834 13d agoI am on AI max 395, comfyUI+qwen models is all you technically need. With today's release, I just built a quick and dirty html that allow simpler prompt use and edits ( via headless comfyui ).. its not bad for a day's work, but a little too unpolished to publish. I would say, try comfyUI first ( complex, but it worked OOTB ).