LyCORIS
bitsandbytes-rocm
LyCORIS | bitsandbytes-rocm | |
---|---|---|
13 | 4 | |
1,983 | 38 | |
- | - | |
9.6 | 8.8 | |
8 days ago | 12 months ago | |
Python | Python | |
Apache License 2.0 | MIT License |
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LyCORIS
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LoRA (LyCORIS) iA3 is amazing (info in 1st comment)
Lycoris is another implementation of LoRA done by KohakuBlueleaf: https://github.com/KohakuBlueleaf/LyCORIS
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Training LORAs locally guide in text form?
Most guides focus on LoRa training as that has been around for longer. But I think LoHa can give better results. But the training is about half as fas it/s and it requires different training settings.
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Guide to DreamBooth / LORA / LyCORIS
I've read in some tutorials that it is best that the value should be 64 or below, also here they suggest to not go over 64 ( https://github.com/KohakuBlueleaf/LyCORIS )
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LyCORIS doesn't work with inpainting models
Does anyone know how to make LyCORIS models (https://github.com/KohakuBlueleaf/LyCORIS) work with inpainting models?
- wtf is a lycoris?
- I wonder what to do with this?
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I'm the creator of LoRA. How can I make it better?
I think it was linked already but this is also relevant for LoRa: https://github.com/KohakuBlueleaf/LyCORIS Nice work!
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LoRA: Low-Rank Adaptation of Large Language Models
There are some WIP evolutions of SD Lora in the works, like locon and lycoris.
https://github.com/KohakuBlueleaf/LyCORIS
- What the hell is a Locon/Loha model?
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SD fine-tuning methods compared: a benchmark
You might want to expand LoRA to include LoCon and LoHa, (and also add a column for VRAM requirements) (Think of it as a more complete LoRA that works for the kernels in the convolutional units rather than just the weights for the feed-forward network), support is still quite limited, but it's starting to pick up steam https://github.com/KohakuBlueleaf/LyCORIS
bitsandbytes-rocm
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Any methods to train using AMD?
Install dependencies like hipblas-devel hipsparse-devel hipcub-devel git python3.10 make libstdc++-devel accelerate, rocm and hip git clone https://github.com/bmaltais/kohya_ss && cd kohya_ss python3.10 -m venv venv source venv/bin/activate pip3 install torch==1.13.1 torchvision==0.14.1 torchtext==0.14.1 torchaudio==0.13.1 --index-url https://download.pytorch.org/whl/rocm5.2 # problems on 2.0.0 last I tried, but kohya gotten updates since then pip3 install --upgrade -r requirements.txt pip3 uninstall tensorflow && pip3 install tensorflow-rocm pip uninstall bitsandbytes && git clone https://github.com/broncotc/bitsandbytes-rocm # bitsandbytes not required if not using adam8? cd bitesandbytes-rocm && nano Makefile # Replace all 3 instances of 5.3.0 with 5.4.3 make hip python3 setup.py install
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How to run Pygmalion on 4.5GB of VRAM with full context size.
There are a lot of ROCm versions of bitsandbytes. For example this one: https://github.com/broncotc/bitsandbytes-rocm The problem is compatibility with most of the requirements. Kobold does a better job than ooba in offering a more streamlined approach for AMD users.
- Is it possible to load a model in 8bit precision with an AMD card? (6700xt)
- Have you got running LoRA training on an AMD GPU?
What are some alternatives?
lora - Using Low-rank adaptation to quickly fine-tune diffusion models.
sd-scripts
LoRA - Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"
bitsandbytes - Accessible large language models via k-bit quantization for PyTorch.
ComfyUI - The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.
GPTQ-for-LLaMa - 4 bits quantization of LLMs using GPTQ
sd-webui-additional-networks
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
kohya_ss
LoRA_Easy_Training_Scripts - A UI made in Pyside6 to make training LoRA/LoCon and other LoRA type models in sd-scripts easy
StableTuner - Finetuning SD in style.