The capabilities of local LLM text-to-image is honestly pretty damn impressive. IMO, I think local image generation is currently ahead of local code generation. I can get an image in seconds locally with the quality being way higher than what I'd expect from a local model. However with coding it's much slower and much less impressive. I'm sure there's a reason for this and I'm not an AI expert so I'll let the smarter folks tell me why, but that's just been my observation thus far.
victorbjorklund•33m ago
I mean I’m sure it’s the reverse for an artist. They would be less impressed with the image and more impressed with the code quality
gedy•5m ago
To generalize, LLMs are great at what you are not skilled at.
mft_•17m ago
I've played with diffusion models on and off since the first release of Stable Diffusion - just for amusement, without a particular goal.
Recently, I've been helping a friend's wife with some basic vector images for her sewing hobby (she has what is essentially a CNC sewing machine) and have been super-impressed with FLUX.1-Kontext, which I've been running on my Macbook Pro with mflux. Its ability to (for example) take a photo of a human or an animal and return a line drawing which is recognisably them (rather than just a generic similarish image as I've experienced with other models) is excellent.
It's an older model now, but (AIUI) has the text-handling features baked in, and in my various testing is very reliable at giving me the outputs that I want, without the randomness I've experienced previously. It's big and relatively slow (~3 mins per 512x512 image edit on my M1 Max Mac) but excellent to work with. It's also very straightforward to set up, without the harness complexity of e.g. comfyui.
hn45e7pbij•33m ago
Image gen you eyeball one frame and stop, code needs hundreds of tokens all correct in sequence, one bad line and the whole thing fails.
Hard_Space•27m ago
Interesting in the example of assembling the Cheers team how the otherwise great result genericizes Shelley Long.
TomGarden•27m ago
Very impressive, and kind of worrying a 7B model can have such capabilities. The implications are huge. And Qwen does no watermarking (yet) yeah?
d2kx•25m ago
God I love the Qwen team. Easily the most diverse set of models from all the Chinese labs. Only Gemini/DeepMind comes close.
mdp2021•21m ago
How do you use this model locally, similarly to using `llama-server -m <model>`?
(Of course I mean: outside direct use of Python, and in the most efficient way.)
embedding-shape•18m ago
Probably 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`
Boy do I love waking up to find a new awesome toy from the Qwen team waiting for me to play with! Pulling it now
trains39472•16m ago
A 7B diffusion model can now render CJK text better than Microsoft Windows.
tomjen3•5m ago
Just think about how recently we got that feature in the official ChatGPT image gen. And now we have that running locally — assuming that is, I can figure out how to get this running on my Mac — blows my mind.
hgufj•13m ago
I am really grateful to the Chinese Labs for open sourcing their best models. If it was left to the Americans, we would be forced to pay obscene API fees to use them.
on the linked GitHub page they list support Diffusers, ComfyUI, vLLM-Omni, SGLang, and LightX2V with links to each
fishfasell•35m ago
victorbjorklund•33m ago
gedy•5m ago
mft_•17m ago
Recently, I've been helping a friend's wife with some basic vector images for her sewing hobby (she has what is essentially a CNC sewing machine) and have been super-impressed with FLUX.1-Kontext, which I've been running on my Macbook Pro with mflux. Its ability to (for example) take a photo of a human or an animal and return a line drawing which is recognisably them (rather than just a generic similarish image as I've experienced with other models) is excellent.
It's an older model now, but (AIUI) has the text-handling features baked in, and in my various testing is very reliable at giving me the outputs that I want, without the randomness I've experienced previously. It's big and relatively slow (~3 mins per 512x512 image edit on my M1 Max Mac) but excellent to work with. It's also very straightforward to set up, without the harness complexity of e.g. comfyui.