MemoryLLM: Plug-n-Play Interpretable Feed-Forward Memory for Transformers
Paper • 2602.00398 • Published • 6
Makwana Paresh
paresh2806
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upvoted a paper 2 days ago
MemoryLLM: Plug-n-Play Interpretable Feed-Forward Memory for Transformers upvoted a changelog 13 days ago
Introducing Buckets: S3-like storage on the HubOrganizations
upvoted a paper 2 days ago
upvoted a changelog 13 days ago
Hugging Face Changelog
Introducing Buckets: S3-like storage on the Hub
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reactedto frumu's post with 👀 about 1 month ago
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691
I’m looking for Mac/Windows/Linux testers and contributors for Tandem, an open-source, local-first AI desktop workspace.
Runs on your machine (works great with local LLMs like Ollama / LM Studio)
Built with Tauri + a sidecar runtime, so it’s a single install
Focused on making agent workflows usable for non-developers (approvals + undo)
If you’re willing to test installs (especially macOS) or poke at bugs, I’d really appreciate it. Repo: https://github.com/frumu-ai/tandem
Runs on your machine (works great with local LLMs like Ollama / LM Studio)
Built with Tauri + a sidecar runtime, so it’s a single install
Focused on making agent workflows usable for non-developers (approvals + undo)
If you’re willing to test installs (especially macOS) or poke at bugs, I’d really appreciate it. Repo: https://github.com/frumu-ai/tandem
reactedto MonsterMMORPG's post with 👀 about 1 month ago
Post
4709
SeedVR2 and FlashVSR+ Studio Level Image and Video Upscaler Pro Released
Tutorial video : https://www.youtube.com/watch?v=bPWsg8DREiM
📂 Resources & Links:
💻 SECourses Ultimate Video and Image Upscaler Pro Download Link : [ https://www.patreon.com/posts/Upscaler-Studio-Pro-150202809 ]
🚆 Requirements Tutorial : https://youtu.be/DrhUHnYfwC0
🛠️ Requirements Written Post : [ https://www.patreon.com/posts/Windows-AI-Requirements-Setup-Guide-111553210 ]
👋 SECourses Discord Channel for 7/24 Support: [ https://bit.ly/SECoursesDiscord ]
It has been long waited to have a studio level video and image upscaler app. Today we have publishing the version 1.0 of SECourses Ultimate Video and Image Upscaler Pro. It is supporting SeedVR2, FlashVSR+, Gan based upscalers, RIFE frame interpolation, full queue system, full batch folder processing, scene / chunked based processing and many more. It is fully working on every cloud and consumer GPUs like RTX 2000, 3000, 4000, 5000 series and H100, H200, B200, RTX PRO 6000. We are installing app with latest Torch and CUDA versions atm all fully automatic with pre-compiled libraries. Even Torch compile is fully and automatically working.
Tutorial video : https://www.youtube.com/watch?v=bPWsg8DREiM
📂 Resources & Links:
💻 SECourses Ultimate Video and Image Upscaler Pro Download Link : [ https://www.patreon.com/posts/Upscaler-Studio-Pro-150202809 ]
🚆 Requirements Tutorial : https://youtu.be/DrhUHnYfwC0
🛠️ Requirements Written Post : [ https://www.patreon.com/posts/Windows-AI-Requirements-Setup-Guide-111553210 ]
👋 SECourses Discord Channel for 7/24 Support: [ https://bit.ly/SECoursesDiscord ]
It has been long waited to have a studio level video and image upscaler app. Today we have publishing the version 1.0 of SECourses Ultimate Video and Image Upscaler Pro. It is supporting SeedVR2, FlashVSR+, Gan based upscalers, RIFE frame interpolation, full queue system, full batch folder processing, scene / chunked based processing and many more. It is fully working on every cloud and consumer GPUs like RTX 2000, 3000, 4000, 5000 series and H100, H200, B200, RTX PRO 6000. We are installing app with latest Torch and CUDA versions atm all fully automatic with pre-compiled libraries. Even Torch compile is fully and automatically working.
- 1 reply
upvoted a paper about 1 month ago
published an article 9 months ago
Article
Why SGLang is a Game-Changer for LLM Workflows
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23
upvoted 2
articles 9 months ago
Article
Vision Language Models Explained
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529
Article
Transformers backend integration in SGLang
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55
reactedto Jaward's post with 👍 9 months ago
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2084
I played around with the new RXTX paper (XX^T) and was able to train nanogpt with 4x4 RXTX matmuls in both attention layer and optimizer🤕
It just works (well I had to add some guardrails) but still saves 5% of memory usage:
The Patch:
- Computes attention scores with a 4x4 blockwise RXTX matmuls (no pytorch dot prod)
- Handles arbitrary sequence lengths by padding to the nearest multiple of 4.
- An RXTX variant of shampoo with params reshaped into 4x4 blocks during each optimizer step.
- Uses 5% less ops
Code: https://github.com/Jaykef/ai-algorithms/blob/main/nanogpt-rxtx.ipynb
Paper: https://arxiv.org/pdf/2505.09814
It just works (well I had to add some guardrails) but still saves 5% of memory usage:
The Patch:
- Computes attention scores with a 4x4 blockwise RXTX matmuls (no pytorch dot prod)
- Handles arbitrary sequence lengths by padding to the nearest multiple of 4.
- An RXTX variant of shampoo with params reshaped into 4x4 blocks during each optimizer step.
- Uses 5% less ops
Code: https://github.com/Jaykef/ai-algorithms/blob/main/nanogpt-rxtx.ipynb
Paper: https://arxiv.org/pdf/2505.09814
reactedto AdinaY's post with 👍 10 months ago
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3194
RoboBrain 2.0🔥 OPEN embedded brain model by BAAIBeijing
BAAI/RoboBrain2.0-7B
✨ 7B - Apache 2.0 / 32B coming soon
✨ Supports multiple images, long videos, and high-resolution visuals
✨ Spatial + temporal reasoning
✨ Real-time memory & scene graphs
BAAI/RoboBrain2.0-7B
✨ 7B - Apache 2.0 / 32B coming soon
✨ Supports multiple images, long videos, and high-resolution visuals
✨ Spatial + temporal reasoning
✨ Real-time memory & scene graphs
upvoted a changelog 10 months ago
Hugging Face Changelog
Static Spaces can now have a build step
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