tf-metal-experiments
ML-Workspace
| tf-metal-experiments | ML-Workspace | |
|---|---|---|
| 5 | 7 | |
| 259 | 3,324 | |
| - | 0.4% | |
| 0.0 | 2.7 | |
| about 2 years ago | 6 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | Apache License 2.0 |
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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.
tf-metal-experiments
- Launch HN: Metal (YC W23) – Embeddings as a Service
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M2 Pro or M2 Max for AI?
My take on Apple M series SOCs: I don’t think any of them can hold a candle to Nvidia GPUs. The M2 Pro is like 1/8th of a 3090 and the M2 Max is 1/5th. https://github.com/tlkh/tf-metal-experiments
- TensorFlow Metal Back End on Apple Silicon Experiments (Just for Fun)
- [N] AMD launches MI200 AI accelerators (2.5x Nvidia A100 FP32 performance)
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[D] How does tensorflow perform on M1 Pro/Max?
Some initial tests going on here: https://github.com/tlkh/tf-metal-experiments
ML-Workspace
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[D] I recently quit my job to start a ML company. Would really appreciate feedback on what we're working on.
Also check out: https://github.com/ml-tooling/ml-workspace, it a nice open source project with lots of packages ready to use.
- ML-Workspace
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Coding for machine learning on Tab S8?
The other option - no reason why you couldn't host something on the desktop machine - web based IDE like R-Studio or Python - have a look at ml-workspace - https://github.com/ml-tooling/ml-workspace that runs in Docker and would provide interfaces for both Python and R, VSCode as well as a GPU accelerated variant for doing Tensorflow etc - either Windows or Linux can support Docker containers (Linux is less trouble apparently - I only have played with it in Linux personally)
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Dynamically spin up VM (based on specific HTTPS request) and stop it once session is over?
It will be a web based IDE dev kit (like Jupyter Hub, or JupyterLab) if you are familiar with them)
- All-in-One Docker Based IDE for Data Science and ML
- Visual Studio Code now available as Web based editor for GitHub repos
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[P] Install or update CUDA, NVIDIA Drivers, Pytorch, Tensorflow, and CuDNN with a single command: Lambda Stack
I'll stick with https://github.com/ml-tooling/ml-workspace, is a docker with all tools installed, also the option of using GPU, so I think is better than only for debian. This way anyone can use it.
What are some alternatives?
Transformer-Explainability - [CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.
JupyterLab - JupyterLab computational environment.
MetalPetal - A GPU accelerated image and video processing framework built on Metal.
Gitpod - DEPRECATED since Gitpod 0.5.0; use https://github.com/gitpod-io/gitpod/tree/master/chart and https://github.com/gitpod-io/gitpod/tree/master/install/helm
HugsVision - HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision
keytotext - Keywords to Sentences
adanet - Fast and flexible AutoML with learning guarantees.
self-hosted - Sentry, feature-complete and packaged up for low-volume deployments and proofs-of-concept
metal
Code-Server - VS Code in the browser
MetalFilters - Instagram filters implemented in Metal
cocalc-docker - DEPRECATED (was -- Docker setup for running CoCalc as downloadable software on your own computer)