Hugging Face's logo
AbstractPhila's picture
12 2 13

AbstractPhila PRO

AbstractPhil
John6666's profile picture evivrus's profile picture Geoion99's profile picture
·
https://civitai.com/user/AbstractPhila

AI & ML interests

datasets, research papers, experimentation, vision, classification, text encoders, tokenization, llms, diffusion, distillation, and more.

Recent Activity

posted an update about 5 hours ago
Lyra, Lune, Cantor, k-simplex, and many relational experiments. https://huggingface.co/spaces/AbstractPhil/sd15-flow-matching-lune Today I will be updating the space to support all three forms of lyra to enable tinkertoying with various other models like flux-schnell and sdxl. It should be noted, I didn't know nvidia actually released a model named LYRA. This model has no association with NVIDIA's LYRA model. This LYRA is full MIT licensed. If necessary I'll rename this model, but I don't think it'll matter. Unlike NORMAL VAE, this VAE was intentionally meant to introduce incorrectness into the correctness that already exists. The concept was to pull towards a goal - t5-xl being the primary goal. https://huggingface.co/AbstractPhil/vae-lyra Lyra is a multimodal MM-VAE prototype meant to encompass a fusion of multiple types of encodings together. Tested with circle of fifths audio and text, multiple text encoders, vision and text encoder, and a few other smaller prototypes that yielded. Lyra has a few direct clip_l and t5_xl prototypes that directly learned to associate clip_l with t5-base. This version worked, so version 2 expanded the concept. https://huggingface.co/AbstractPhil/vae-lyra-sdxl-t5xl is another prototype using CLIP_L and CLIP_G fused with T5_XL for the first version, directly utilizing projection with minimal geometric and cantor assistance. The shared layers ended up teaching CLIP_L how to be CLIP_G and the output ended up warping too much for SDXL or SD15 to understand. https://huggingface.co/AbstractPhil/vae-lyra-xl-adaptive-cantor Utilizing adapative cantor is the successful prototype where CLIP_L and CLIP_G learned independent structures internally, where CLIP_L and T5_XL learned a route with CLIP_G and T5_XL in parallel conjunction. This enabled two entirely divergent opinions, and thus enables the t5-xl to manipulate either the clip_l or the clip_g for models like FLUX-SCHNELL or SDXL. Each lyra has a purpose, and each purpose matters.
updated a model about 9 hours ago
AbstractPhil/liminal-staircase-v2
updated a model about 9 hours ago
AbstractPhil/liminal-staircase-v2
View all activity

Organizations

DeepGHS's profile picture BangumiBase's profile picture Abstract Powered Research's profile picture