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Can it run on a 4080 but slower, or is the vram a limitation?

by boppo1 2y ago

dvrp 2y ago
They don't mention that and I don't have one — can you try for yourself and let us know? I think you can get it from Huggingface or GH @ https://github.com/Tencent/Hunyuan3D-2 https://github.com/Tencent/Hunyuan3D-2
- fancyfredbot 2y ago
  They mention "It takes 6 GB VRAM for shape generation and 24.5 GB for shape and texture generation in total." So based on this your 4080 can do shape but not texture generation.
  - boppo1 2y ago
    Nnice, that's all i needed anyway.
thot_experiment 2y ago
almost certainly, i haven't tried the most recent models but i have used hy3d2 and hy3d2-fast a lot and they're quite light to inference. You're gonna spend more time decoding the latent than you will inferencing. Takes about 6gb vram on my machine, I can't imagine these will be heavier.
llm_nerd 2y ago
It can run on a 4080 if you divide and conquer. I just ran a set on my 3060 (12GB), although I have my own script which does each step separately as each stage uses from 6 - 12GB of VRAM. -loads the diffusion model to go from text to an image and then generate a varied series of images based upon my text. One of the most powerful features of this tool, in my opinion, is text to mesh, and to do this it uses a variant of Stable Diffusion to create 2D images as a starting point, then returning to the image to mesh pipeline. If you already have an image this part obviously isn't necessary. -frees the diffusion model from memory. Then for each image I- -load the image to mesh model, which takes approximately 12GB of VRAM. Generate a mesh -free the image to mesh model -load the mesh + image to textured mesh model. Texture the mesh -free the mesh + image to textured mesh model It adds a lot of I/O between each stage, but with super fast SSDs it just isn't a big problem.
- llm_nerd 2y ago
  Just as one humorous aside, if you use the text to mesh pipeline, as mentioned the first stage is simply a call to a presumably fine-tuned variant of stable diffusion with your text and the following prompts (translated from Simplified Chinese)- Positive: "White background, 3D style, best quality" Negative: "text, closeup, cropped, out of frame, worst quality, low quality, JPEG artifacts, PGLY, duplicate, morbid, mutilated, extra fingers, mutated hands, bad hands, bad face, mutation, deformed, blurry, dehydrated, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck" Thought that was funny.

Can it run on a 4080 but slower, or is the vram a limitation?

by boppo1 2y ago

Can it run on a 4080 but slower, or is the vram a limitation?

dvrp 2y ago

They don't mention that and I don't have one — can you try for yourself and let us know? I think you can get it from Huggingface or GH @ https://github.com/Tencent/Hunyuan3D-2 https://github.com/Tencent/Hunyuan3D-2

fancyfredbot 2y ago
They mention "It takes 6 GB VRAM for shape generation and 24.5 GB for shape and texture generation in total." So based on this your 4080 can do shape but not texture generation.
- boppo1 2y ago
  Nnice, that's all i needed anyway.

thot_experiment 2y ago

almost certainly, i haven't tried the most recent models but i have used hy3d2 and hy3d2-fast a lot and they're quite light to inference. You're gonna spend more time decoding the latent than you will inferencing. Takes about 6gb vram on my machine, I can't imagine these will be heavier.

llm_nerd 2y ago

It can run on a 4080 if you divide and conquer. I just ran a set on my 3060 (12GB), although I have my own script which does each step separately as each stage uses from 6 - 12GB of VRAM. -loads the diffusion model to go from text to an image and then generate a varied series of images based upon my text. One of the most powerful features of this tool, in my opinion, is text to mesh, and to do this it uses a variant of Stable Diffusion to create 2D images as a starting point, then returning to the image to mesh pipeline. If you already have an image this part obviously isn't necessary. -frees the diffusion model from memory. Then for each image I- -load the image to mesh model, which takes approximately 12GB of VRAM. Generate a mesh -free the image to mesh model -load the mesh + image to textured mesh model. Texture the mesh -free the mesh + image to textured mesh model It adds a lot of I/O between each stage, but with super fast SSDs it just isn't a big problem.

llm_nerd 2y ago
Just as one humorous aside, if you use the text to mesh pipeline, as mentioned the first stage is simply a call to a presumably fine-tuned variant of stable diffusion with your text and the following prompts (translated from Simplified Chinese)- Positive: "White background, 3D style, best quality" Negative: "text, closeup, cropped, out of frame, worst quality, low quality, JPEG artifacts, PGLY, duplicate, morbid, mutilated, extra fingers, mutated hands, bad hands, bad face, mutation, deformed, blurry, dehydrated, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck" Thought that was funny.