The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning. Learn more →
Top 7 Python tpu Projects
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skypilot
SkyPilot: Run LLMs, AI, and Batch jobs on any cloud. Get maximum savings, highest GPU availability, and managed execution—all with a simple interface.
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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DECIMER-Image_Transformer
DECIMER: Deep Learning for Chemical Image Recognition using Efficient-Net V2 + Transformer
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evopose2d
EvoPose2D is a two-stage human pose estimation model that was designed using neuroevolution. It achieves state-of-the-art accuracy on COCO.
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xpk
xpk (Accelerated Processing Kit, pronounced x-p-k,) is a software tool to help Cloud developers to orchestrate training jobs on accelerators such as TPUs and GPUs on GKE.
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
Project mention: Ask HN: Most efficient way to fine-tune an LLM in 2024? | news.ycombinator.com | 2024-04-04
Project mention: A user-built manual on using TPUs for AI and LLMs on Google Cloud | news.ycombinator.com | 2023-08-04
Project mention: Show HN: Elodin – A better framework for physics simulation | news.ycombinator.com | 2024-03-06You are completely correct; right now it is just mechanics that we have built out. But, there isn't any theoretical reason you couldn't use this framework for other types of simulation. In particular, the Monte Carlo runner is super flexible. Since we are based on JAX you can utilize a ton of the tooling that others have built in the physics space like https://github.com/tumaer/JAXFLUIDS or https://github.com/DifferentiableUniverseInitiative/jax_cosm... . The goal right now though is pretty firmly focused on controls engineers and their needs, but we envision this becoming broadly used.
I’ll take this opportunity to mention our research scaling StyleGAN 2 to larger datasets (using LAION) on food images, leveraging free TPU compute through the TRC program.
We trained for 36 days on a v4-8 on 558k images.
https://nyx-ai.github.io/stylegan2-flax-tpu/
We were hopeful GANs would beat diffusion models when trained on specific domains. But we’ve now switched to Stable Diffusion and Dreambooth training which has proven more much efficient for this purpose.
I still have hopes for GANs! I miss their insane inference speed.
There is a lot of work to make the actual infrastructure and lower level management of lots and lots of GPUs/TPUs open as well - my team focuses on making the infrastructure bit at least a bit more approachable on GKE and Kubernetes.
https://github.com/GoogleCloudPlatform/ai-on-gke/tree/main
and
https://github.com/google/xpk (a bit more focused on HPC, but includes AI)
and
https://github.com/stas00/ml-engineering (not associated with GKE, but describes training with SLURM)
The actual training is still a bit of a small pool of very experienced people, but it's getting better. And every day serving models gets that much faster - you can often simply draft on Triton and TensorRT-LLM or vLLM and see significant wins month to month.
Python tpu related posts
- Understand how transformers work by demystifying all the math behind them
- [P] Why the Original Transformer Figure Is Wrong, And Some Other Interesting Tidbits
- Why the Original Transformer LLM Figure Is Wrong, and Other Interesting Tidbits
- What Are Transformer Models and How Do They Work?
- This Food Does Not Exist
- [P] This Food Does Not Exist, Updated
- Show HN: Food Does Not Exist, Updated
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A note from our sponsor - WorkOS
workos.com | 24 Apr 2024
Index
What are some of the best open-source tpu projects in Python? This list will help you:
Project | Stars | |
---|---|---|
1 | skypilot | 5,602 |
2 | tpu-starter | 452 |
3 | JAXFLUIDS | 245 |
4 | DECIMER-Image_Transformer | 160 |
5 | stylegan2-flax-tpu | 130 |
6 | evopose2d | 82 |
7 | xpk | 52 |
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