Machine Learning - AI - Tensorflow - Keras - NVidia - Google
active 2023-10-01 → 2026-02-07 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 861 days from 2023-10-01 to 2026-02-07. Pushes: 84 total, peak 9 in a day. Pull requests: 2 total, peak 2 in a day. Issues: 42 total, peak 4 in a day. Comments: 124 total, peak 9 in a day. Stars: 0 total, peak 0 in a day.
- Pushes
- Pull requests
- Issues
- Comments
- Stars
Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| obriensystems | 249 | 83 | 2 | 122 |
| fmichaelobrien | 3 | 1 | 0 | 2 |
Recent activity
Latest issues, pull requests and releases
- Issue comment#5obriensystems2026-02-07 17:49Work with Google C4 dataset of common crawl
- Issue#51obriensystems2026-01-08 03:10Archetypes using this tensorflow example
- Issue#51obriensystems2026-01-08 03:10Archetypes using this tensorflow example
- Issue comment#48obriensystems2025-11-09 23:34Tensorflow 2.14 on NVIDIA DGX Spark GB10 on CUDA 13 - ARM64
- Issue comment#48obriensystems2025-11-09 23:02Tensorflow 2.14 on NVIDIA DGX Spark GB10 on CUDA 13 - ARM64
- Issue#45obriensystems2025-08-07 17:08OpenAI OSS models on CUDA
- Issue comment#33obriensystems2025-08-07 17:06Tensorflow 2.14 on P1Gen6 ADA AD104 NVIDIA RTX-3500 ada GPU - OK using tensorflow/tensorflow:2.14.0-gpu on CUDA 12.6
- Issue comment#37obriensystems2025-03-02 02:50DeepSeek R1 14b on NVIDIA 48G RTX-A6000, Apple M2 Ultra 60 core 64G or Apple M4 Max 40 core 48G compared to OpenAI o1 pro
- Issue comment#37obriensystems2025-03-02 02:47DeepSeek R1 14b on NVIDIA 48G RTX-A6000, Apple M2 Ultra 60 core 64G or Apple M4 Max 40 core 48G compared to OpenAI o1 pro
- Issue comment#44obriensystems2025-03-02 01:37running ollama as a remote LLM server
- Issue#44obriensystems2025-03-01 23:51running ollama as a remote LLM server
- Issue comment#37obriensystems2025-03-01 23:40DeepSeek R1 14b on NVIDIA 48G RTX-A6000, Apple M2 Ultra 60 core 64G or Apple M4 Max 40 core 48G compared to OpenAI o1 pro
- Issue#42obriensystems2025-02-17 16:14Distributed Inference on NVIDIA GPUs using TensorFlow 2.18
- Issue comment#32obriensystems2025-02-17 01:39Tensorflow 2 on Metal - Apple Silicon M4 Max 12/4 40 core GPU
- Issue comment#37obriensystems2025-02-16 23:51DeepSeek R1 14b on NVIDIA 48G RTX-A6000, Apple M2 Ultra 60 core 64G or Apple M4 Max 40 core 48G compared to OpenAI o1 pro
- Issue comment#37obriensystems2025-02-16 23:43DeepSeek R1 14b on NVIDIA 48G RTX-A6000 or Apple M4 Max 40 core 48G compared to OpenAI o1 pro
- Issue comment#36obriensystems2025-02-16 23:03Tensorflow 2.14 on Apple Silicon CPU (not GPU) - for performance comparison
- Issue#41obriensystems2025-02-11 21:49Distributed inference on M4 Macs using PyTorch on thunderbolt 5 40-80 Gbps networking
- Issue comment#40obriensystems2025-02-11 00:50Distributed inference on M4 Macs using TensorFlow on thunderbolt 5 40-80 Gbps networking
- Issue comment#40obriensystems2025-02-10 23:15Distributed inference on M4 Macs using TensorFlow on thunderbolt 5 40-80 Gbps networking
- Issue comment#40obriensystems2025-02-10 22:19Distributed inference on M4 Macs using TensorFlow on thunderbolt 5 40-80 Gbps networking
- Issue comment#40obriensystems2025-02-09 15:12Distributed inference on M4 Macs using TensorFlow
- Issue comment#40obriensystems2025-02-09 15:10Distributed inference on M4 Macs using TensorFlow
- Issue#40obriensystems2025-02-09 15:06Distributed inference on M4 Macs using TensorFlow
- Pull request#39obriensystems2025-01-31 21:00
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.