cloneofsimo/lora
Using Low-rank adaptation to quickly fine-tune diffusion models.
Language: Jupyter Notebook
#diffusion #fine_ #lora #stable_diffusion
Stars: 316 Issues: 7 Forks: 24
https://github.com/cloneofsimo/lora
Using Low-rank adaptation to quickly fine-tune diffusion models.
Language: Jupyter Notebook
#diffusion #fine_ #lora #stable_diffusion
Stars: 316 Issues: 7 Forks: 24
https://github.com/cloneofsimo/lora
GitHub
GitHub - cloneofsimo/lora: Using Low-rank adaptation to quickly fine-tune diffusion models.
Using Low-rank adaptation to quickly fine-tune diffusion models. - cloneofsimo/lora
mit-han-lab/nunchaku
SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models
Language: Cuda
#diffusion_models #flux #genai #lora #mlsys #quantization
Stars: 249 Issues: 10 Forks: 13
https://github.com/mit-han-lab/nunchaku
SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models
Language: Cuda
#diffusion_models #flux #genai #lora #mlsys #quantization
Stars: 249 Issues: 10 Forks: 13
https://github.com/mit-han-lab/nunchaku
GitHub
GitHub - mit-han-lab/nunchaku: SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models
SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models - mit-han-lab/nunchaku