tf-metal-experiments
adanet
tf-metal-experiments | adanet | |
---|---|---|
5 | 2 | |
259 | 3,470 | |
- | -0.1% | |
0.0 | 0.0 | |
about 2 years ago | 5 months ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | 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.
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
adanet
- alguém sabe alguma coisa sobre AdaNetQuantum?
-
Show HN: AutoAI
Looks like a nice project. I just bookmarked it to try sometime.
At a previous job, my boss wanted me to spend time on AutoML. I based my work on Google’s AdaNet [1] that did architecture search inside a single TensorFlow session. Unfortunately that project seems to have been abandoned.
[1] https://github.com/tensorflow/adanet
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.
autokeras - AutoML library for deep learning
MetalPetal - A GPU accelerated image and video processing framework built on Metal.
ai-seed - 1000+ ready code templates to kickstart your next AI experiment
HugsVision - HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision
automlbenchmark - OpenML AutoML Benchmarking Framework
ML-Workspace - 🛠 All-in-one web-based IDE specialized for machine learning and data science.
H2O - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
metal
autoai - Python based framework for Automatic AI for Regression and Classification over numerical data. Performs model search, hyper-parameter tuning, and high-quality Jupyter Notebook code generation.
MetalFilters - Instagram filters implemented in Metal