An absolutely incredible experience with this model, the sheer speed alongside its massive data set. Hard not to be impressed and should quickly become a favourite for people who like talkative and fast models.
Enda Rochford
RochyRoch
AI & ML interests
None yet
Recent Activity
commented on
an
article
13 days ago
Ling-mini-2.0: Mini-Sized, Maximum Efficiency
upvoted
an
article
13 days ago
Ling-mini-2.0: Mini-Sized, Maximum Efficiency
new activity
7 months ago
lmstudio-community/SmolLM3-3B-GGUF:issue with the model's prompt template
Organizations
None yet
commented on
Ling-mini-2.0: Mini-Sized, Maximum Efficiency
13 days ago
upvoted
an
article
13 days ago
Article
Ling-mini-2.0: Mini-Sized, Maximum Efficiency
•
1
issue with the model's prompt template
1
#1 opened 7 months ago
by
RochyRoch
New activity in
SauRabM/llama-3-8b-Instruct-bnb-4bit-saurab-petitioner-respondent-final
10 months ago
Great model
2
#1 opened 11 months ago
by
RochyRoch
The weirdest interactions with an LLM
7
#1 opened 11 months ago
by
RochyRoch
liked
a
model
10 months ago
liked
3
models
11 months ago
reacted to
elismasilva's
post with 🔥
12 months ago
Post
3717
Mixture-of-Diffusers pipeline tiling for SDXL
This strives to provide a better tool for image composition by using several diffusion processes in parallel, each configured with a specific prompt and settings, and focused on a particular region of the image. The mixture of diffusion processes is done in a way that harmonizes the generation process, preventing "seam" effects in the generated image. Using several diffusion processes in parallel has also practical advantages when generating very large images, as the GPU memory requirements are similar to that of generating an image of the size of a single tile.
elismasilva/mixture-of-diffusers-sdxl-tiling
This strives to provide a better tool for image composition by using several diffusion processes in parallel, each configured with a specific prompt and settings, and focused on a particular region of the image. The mixture of diffusion processes is done in a way that harmonizes the generation process, preventing "seam" effects in the generated image. Using several diffusion processes in parallel has also practical advantages when generating very large images, as the GPU memory requirements are similar to that of generating an image of the size of a single tile.
elismasilva/mixture-of-diffusers-sdxl-tiling
liked
a
Space
12 months ago
