yauaa
ml-stable-diffusion
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| yauaa | ml-stable-diffusion | |
|---|---|---|
| 2 | 45 | |
| 728 | 16,111 | |
| - | 1.9% | |
| 9.7 | 7.4 | |
| 4 days ago | 21 days ago | |
| Java | Python | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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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.
yauaa
- December 5, 2022: FLiP Stack Weekly
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How to Parse User Agents with a Snowflake UDF in dbt
UDF code in the main project: https://github.com/nielsbasjes/yauaa/blob/master/udfs/snowflake/src/main/java/nl/basjes/parse/useragent/snowflake/ParseUserAgent.java
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?
Apache Flink - Apache Flink
MochiDiffusion - Run Stable Diffusion on Mac natively
flink-faker - A data generator source connector for Flink SQL based on data-faker.
ml-ane-transformers - Reference implementation of the Transformer architecture optimized for Apple Neural Engine (ANE)
snowflake-kafka-connector - Snowflake Kafka Connector (Sink Connector)
modelscope - ModelScope: bring the notion of Model-as-a-Service to life.
nussknacker - Low-code tool for automating actions on real time data | Stream processing for the users.
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.
DataflowTemplates - Cloud Dataflow Google-provided templates for solving in-Cloud data tasks
fast-stable-diffusion - fast-stable-diffusion + DreamBooth
nifi-extracttext-processor - Apache NiFi Custom Processor Extracting Text From Files with Apache Tika
stable-diffusion-webui - Stable Diffusion web UI