fastjson2
ml-stable-diffusion
| fastjson2 | ml-stable-diffusion | |
|---|---|---|
| 2 | 45 | |
| 3,454 | 16,245 | |
| 2.1% | 1.5% | |
| 9.8 | 7.4 | |
| about 13 hours ago | 12 days ago | |
| Java | Python | |
| Apache License 2.0 | MIT License |
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.
fastjson2
- FLaNK Stack Weekly for 20 June 2023
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Serverless Speed: Rust vs. Go, Java, and Python in AWS Lambda Functions
https://github.com/alibaba/fastjson2/wiki/fastjson_benchmark Alibaba has a fastjson2 that claims to be a lot faster.
ml-stable-diffusion
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Show HN: Run Stable Diffusion Directly on iPhone
Not sure how that got in here. Apple released CoreML Stable Diffusion library a little over a year ago [1]. Hugging Face released their version of the example app for the CoreML Stable Diffusion library [2].
The app should be able to run on iPhone 14 Pro, I believe the requirements is about 6-8Gb of RAM. And I was not able to run it on iPhone 13 Mini, because it has only 4Gb of RAM.
- [1] https://github.com/apple/ml-stable-diffusion
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Apple releases MLX; has working Stable Diffusion example
Where are you seeing a Stable Diffusion example? I'm familiar with Apple's CoreML Implementation of StableDiffusion, but is there something else in the SD world available for download now as part of MLX?
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Stable Diffusion XL on iPhone with Core ML
Other features and improvements to the repo https://github.com/apple/ml-stable-diffusion
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FLaNK Stack Weekly for 20 June 2023
M1! https://github.com/apple/ml-stable-diffusion
- Apple Introduces M2 Ultra with up to 192GB Unified Memory - LLM powerhouse?
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Need help choosing between two laptops
M2 MBA can run Stable Diffusion and LLaMa comfortably, which means generating your potential game/image asset locally. They're pretty much impractical in 7340.
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Speed Is All You Need: On-Device Acceleration of Large Diffusion Models
Interestingly these are OpenCL kernels so in theory some of the optimizations might run out-of-the-box on CPUs.
It would be instructive to compare their speedups on the iPhone to the Apple CoreML implementation: https://github.com/apple/ml-stable-diffusion
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Is it worth buying a used M1 Mac for stable diffusion when you have iPad M1 but Intel Mac
Stable Diffusion runs great on my M1 Macs. The Draw Things app makes it really easy to run too. You also can’t disregard that Apple’s M chips actually have dedicated neural processing for ML/AI. This actual makes a Mac more affordable in this category because you don’t need to purchase a beefy graphics card. Not to mention that Apple has even optimized their software specifically for Stable Diffusion (related GitHub). Draw Things can take advantage of this. There’s a few guides to running the web UI on M1 too. I prefer the Draw Things app because of how easy it is to use, but the web UI is also nice because of all of the plugins and workflows that the community has built over time.
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Stable diffusion for Apple silicon
LINKS: ml-stable-diffusion: https://github.com/apple/ml-stable-diffusion Diffusers (HuggingFace Mac App): https://apps.apple.com/app/diffusers/id1666309574?mt=12
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Apple: Transformer architecture optimized for Apple Silicon
So, is Stable Diffusion working finally on TPU or not? DiffusionBee uses GPU and running this https://github.com/apple/ml-stable-diffusion with CPU_AND_NE just segfaults
What are some alternatives?
jackson-databind - General data-binding package for Jackson (2.x): works on streaming API (core) implementation(s)
MochiDiffusion - Run Stable Diffusion on Mac natively
java-json-benchmark - Performance testing of serialization and deserialization of Java JSON libraries
ml-ane-transformers - Reference implementation of the Transformer architecture optimized for Apple Neural Engine (ANE)
modelscope - ModelScope: bring the notion of Model-as-a-Service to life.
StanfordQuadruped
pulsar-recipes - A StreamNative library containing a collection of recipes that are implemented on top of the Pulsar client to provide higher-level functionality closer to the application domain.
json-data-storage - 🚀 The Shared Preferences API for Java
fast-stable-diffusion - fast-stable-diffusion + DreamBooth
simdjson-java - A Java version of simdjson, a high-performance JSON parser utilizing SIMD instructions
stable-diffusion-webui - Stable Diffusion web UI