kernl
diffusers
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kernl | diffusers | |
---|---|---|
8 | 266 | |
1,446 | 22,020 | |
1.9% | 5.7% | |
1.5 | 9.9 | |
about 1 month ago | about 2 hours ago | |
Jupyter Notebook | Python | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
kernl
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[P] Get 2x Faster Transcriptions with OpenAI Whisper Large on Kernl
I periodically check kernl.ai to see whether the documentation and tutorial sections have been expanded. My advice is put some real effort and focus in to examples and tutorials. It is key for an optimization/acceleration library. 10x-ing the users of a library like this is much more likely to come from spending 10 out of every 100 developer hours writing tutorials, as opposed to spending those 8 or 9 of those tutorial-writing hours on developing new features which only a small minority understand how to apply.
Kernl repository: https://github.com/ELS-RD/kernl
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[P] BetterTransformer: PyTorch-native free-lunch speedups for Transformer-based models
FlashAttention + quantization has to the best of knowledge not yet been explored, but I think it would a great engineering direction. I would not expect to see this any time soon natively in PyTorch's BetterTransformer though. /u/pommedeterresautee & folks at ELS-RD made an awesome work releasing kernl where custom implementations (through OpenAI Triton) could maybe easily live.
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[D] How to get the fastest PyTorch inference and what is the "best" model serving framework?
Check https://github.com/ELS-RD/kernl/blob/main/src/kernl/optimizer/linear.py for an example.
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[P] Up to 12X faster GPU inference on Bert, T5 and other transformers with OpenAI Triton kernels
https://github.com/ELS-RD/kernl/issues/141 > Would it be possible to use kernl to speed up Stable Diffusion?
Quite surprisingly, RMSNorm bring a huge unexpected speedup on what we already had! If you want to follow this work: https://github.com/ELS-RD/kernl/pull/107
Scripts are here: https://github.com/ELS-RD/kernl/tree/main/experimental/benchmarks
We are releasing Kernl under Apache 2 license, a library to make PyTorch models inference significantly faster. With 1 line of code we applied the optimizations and made Bert up to 12X faster than Hugging Face baseline. T5 is also covered in this first release (> 6X speed up generation and we are still halfway in the optimizations!). This has been possible because we wrote custom GPU kernels with the new OpenAI programming language Triton and leveraged TorchDynamo.
diffusers
- Making a ControlNet inpaint for sdxl
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Stable Diffusion Gets a Major Boost with RTX Acceleration
For developers, TensorRT support also exists for the diffusers library via community pipelines. [1] It's limited, but if you're only supporting a subset of features, it can help.
In general, these insane speed boosts comes at the cost of bleeding edge features.
[1] https://github.com/huggingface/diffusers/blob/28e8d1f6ec82a6...
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I Made Stable Diffusion XL Smarter by Finetuning It on Bad AI-Generated Images
Merging LoRAs is essentially taking a weighted average of the LoRA adapter weights. It's more common in other UIs.
diffusers is working on a PR for it: https://github.com/huggingface/diffusers/pull/4473
- [SDXL] Simplified explanation of aesthetics score
- Automatic1111 - Multiple GPUs
- SDXL usage warning (Official workflow endorsed by ComfyUI for SDXL in the works)
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Using Stable Diffusion XL with Vladmandic
pip uninstall diffusers && pip install git+https://github.com/huggingface/diffusers.git pip install invisible_watermark
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Just hit 50.73 it/s basic 512x512 image gen with no tricks
I did add: https://github.com/huggingface/diffusers/issues/3950 for that last issue I found. I need to do a full write up on the collected set of things. But sleep is needed now. :-)
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Open source lib to generate qrcodes with stable diffusion and controlnet (link in comments)
Thanks! I just made this colab thanks to this PR which added start/stop support to show how to use the controlnet pipeline to generate qr code using only diffusers
What are some alternatives?
stable-diffusion-webui - Stable Diffusion web UI
stable-diffusion - A latent text-to-image diffusion model
lora - Using Low-rank adaptation to quickly fine-tune diffusion models.
invisible-watermark - python library for invisible image watermark (blind image watermark)
automatic - SD.Next: Advanced Implementation of Stable Diffusion and other Diffusion-based generative image models
Dreambooth-Stable-Diffusion - Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) by way of Textual Inversion (https://arxiv.org/abs/2208.01618) for Stable Diffusion (https://arxiv.org/abs/2112.10752). Tweaks focused on training faces, objects, and styles.
sd-webui-additional-networks
sd-webui-modelscope-text2video - Auto1111 extension consisting of implementation of text2video diffusion models (like ModelScope or VideoCrafter) using only Auto1111 webui dependencies [Moved to: https://github.com/deforum-art/sd-webui-text2video]
LoRA - Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"
gradio - Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
fast-stable-diffusion - fast-stable-diffusion + DreamBooth
bitsandbytes - Accessible large language models via k-bit quantization for PyTorch.