HauhauCS/Gemma-4-E4B-Uncensored-HauhauCS-Aggressive
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reacted to appvoid's post with 🔥 11 days ago
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1410
A Small Model is All You Need. Meet
After 3 years of experiments, we are finally releasing our flagship tiny model: **palmer-006**.
If you are building for edge hardware, SBCs (Raspberry Pi, etc.), or low-power devices, this is for you. Inspired by Andrej Karpathy's idea of a self-contained "cognitive core," we wanted to see how much power we could pack into a sub-100M parameter footprint.
🧠 **How we "Palmerized" it:**
We believe in starting our experiments with the absolute strongest baseline possible.
1. Light fine-tuning on highly curated data
2. Model merging
3. Another light fine-tuning round
4. Adjusted Mamba for maximum token speed ⚡️
⚠️ *Note: This is a foundational language model. It has not been instruction-tuned yet!*
Also, since this needs instruction tuning next to become a chat assistant—**what dataset would you recommend we use for the instruct tune?**
---
🔗 **Quick Links & Info:**
* **License:** Open for research, education, hobby, and modification! (For commercial use/hosted APIs, shoot an email to nosoyhackercodigo@gmail.com. *PS: Donators can claim a free commercial license!*)
* **Attribution:** Built using AI tech from the Technology Innovation Institute (TII).
Can't wait to see what you build at the edge. Let me know your prompt completions below! 👇
appvoid/palmer-006
palmer-006 (90M)After 3 years of experiments, we are finally releasing our flagship tiny model: **palmer-006**.
If you are building for edge hardware, SBCs (Raspberry Pi, etc.), or low-power devices, this is for you. Inspired by Andrej Karpathy's idea of a self-contained "cognitive core," we wanted to see how much power we could pack into a sub-100M parameter footprint.
🧠 **How we "Palmerized" it:**
We believe in starting our experiments with the absolute strongest baseline possible.
1. Light fine-tuning on highly curated data
2. Model merging
3. Another light fine-tuning round
4. Adjusted Mamba for maximum token speed ⚡️
⚠️ *Note: This is a foundational language model. It has not been instruction-tuned yet!*
Also, since this needs instruction tuning next to become a chat assistant—**what dataset would you recommend we use for the instruct tune?**
---
🔗 **Quick Links & Info:**
* **License:** Open for research, education, hobby, and modification! (For commercial use/hosted APIs, shoot an email to nosoyhackercodigo@gmail.com. *PS: Donators can claim a free commercial license!*)
* **Attribution:** Built using AI tech from the Technology Innovation Institute (TII).
Can't wait to see what you build at the edge. Let me know your prompt completions below! 👇
appvoid/palmer-006
- 10 replies
reacted to SeaWolf-AI's post with ❤️ 5 months ago
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8196
🚀 Introducing MARL — Runtime Middleware That Reduces LLM Hallucination Without Fine-Tuning
Now available on PyPI · GitHub · ClawHub · HuggingFace
AI models sense they could be wrong, but they can't actually fix what's broken.
🤗 Live A/B test: VIDraft/MARL
We evaluated 9 SOTA models (GPT-5.2, Claude Opus 4.6, Gemini 3 Pro, etc.) across 1,800 assessments in FINAL Bench and found a 39.2%p gap between "recognizing potential errors (MA=0.694)" and "actually finding and fixing them (ER=0.302)."
MARL (Model-Agnostic Runtime Middleware for LLMs) was built to close this metacognitive gap. It decomposes a single LLM call into a 5-stage expert pipeline (Hypothesis → Solver → Auditor → Adversarial Verifier → Synthesizer), transforming "answer in one shot" into "think, doubt, correct, and rewrite."
No weight modification — works instantly with GPT-5.4, Claude, Gemini, Llama, or any OpenAI API-compatible LLM by changing one line: base_url. Ships with 9 domain-specific emergence engines (invention, pharma, genomics, chemistry, ecology, law, and more — 5,538 expert data items) activated by a simple tag like model="gpt-5.4::pharma".
pip install marl-middleware
MARL is also officially registered on ClawHub, the skill marketplace of OpenClaw — an AI agent platform with 260K+ developers and 3,200+ skills. It's the first middleware in the Reasoning Enhancement category. One command — clawhub install marl-middleware — gives your AI agent a metacognition upgrade.
📝 Technical deep dive: https://huggingface.co/blog/FINAL-Bench/marl-middleware
📦 PyPI: https://pypi.org/project/marl-middleware/
🐙 GitHub: https://github.com/Vidraft/MARL
🦀 ClawHub: https://clawhub.ai/Cutechicken99/marl-middleware
#MARL #LLM #Hallucination #Metacognition #MultiAgent #AIMiddleware #FINALBench #OpenClaw #ClawHub #PyPI #AGI #HuggingFace #ReasoningAI #SelfCorrection #GlassBoxAI
Now available on PyPI · GitHub · ClawHub · HuggingFace
AI models sense they could be wrong, but they can't actually fix what's broken.
🤗 Live A/B test: VIDraft/MARL
We evaluated 9 SOTA models (GPT-5.2, Claude Opus 4.6, Gemini 3 Pro, etc.) across 1,800 assessments in FINAL Bench and found a 39.2%p gap between "recognizing potential errors (MA=0.694)" and "actually finding and fixing them (ER=0.302)."
MARL (Model-Agnostic Runtime Middleware for LLMs) was built to close this metacognitive gap. It decomposes a single LLM call into a 5-stage expert pipeline (Hypothesis → Solver → Auditor → Adversarial Verifier → Synthesizer), transforming "answer in one shot" into "think, doubt, correct, and rewrite."
No weight modification — works instantly with GPT-5.4, Claude, Gemini, Llama, or any OpenAI API-compatible LLM by changing one line: base_url. Ships with 9 domain-specific emergence engines (invention, pharma, genomics, chemistry, ecology, law, and more — 5,538 expert data items) activated by a simple tag like model="gpt-5.4::pharma".
pip install marl-middleware
MARL is also officially registered on ClawHub, the skill marketplace of OpenClaw — an AI agent platform with 260K+ developers and 3,200+ skills. It's the first middleware in the Reasoning Enhancement category. One command — clawhub install marl-middleware — gives your AI agent a metacognition upgrade.
📝 Technical deep dive: https://huggingface.co/blog/FINAL-Bench/marl-middleware
📦 PyPI: https://pypi.org/project/marl-middleware/
🐙 GitHub: https://github.com/Vidraft/MARL
🦀 ClawHub: https://clawhub.ai/Cutechicken99/marl-middleware
#MARL #LLM #Hallucination #Metacognition #MultiAgent #AIMiddleware #FINALBench #OpenClaw #ClawHub #PyPI #AGI #HuggingFace #ReasoningAI #SelfCorrection #GlassBoxAI
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reacted to AdinaY's post with ❤️ 7 months ago
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1875
Chinese open source AI in December 2025 was about the stack coming together: open, end to end, and ready to ship 🔥
https://huggingface.co/collections/zh-ai-community/december-2025-china-open-source-highlights
✨ Big wave of foundation models: still scaling, but efficiency, reasoning, and deployment now matter more than size
- DeepSeek-V3.2
- Z.ai GLM-4.7
- MiniMax-M2.1
- Xiaomi: MiMo-V2-Flash
✨ Multimodal reasoning is now default
- Z.ai GLM-4.6V
- Z.ai AutoGLM-Phone 9B
- Bytedance: Dolphin-v2
✨ Image & video: editable assets and real workflows
- Qwen-Image-Layered / Image-2512
- Meituan: LongCat-Image & Image Edit
- AIDC: Ovis-Image-7B
- Live-Avatar / LongCat-Video-Avatar
- HY-WorldPlay / RealVideo
✨ Audio goes edge ready
- GLM-ASR-Nano / Fun-ASR-Nano
- GLM-TTS / VoxCPM1.5
- CosyVoice 0.5B
✨ The quiet backbone: data & infrastructure
- Finch (FinWorkBench)
- Tencent ARC: TimeLens-100K
- BIGAI: TongSIM-Asset
- MiniMax: VTP-Base
✨ Also congrats on Minimax and Z.ai announced their IPOs and Moonshot announced a new $500M funding round 🔥
Like everyone else, I was OOO at the end of December, so feel free to share (in comments or PR) any I missed in this list!
https://huggingface.co/collections/zh-ai-community/december-2025-china-open-source-highlights
✨ Big wave of foundation models: still scaling, but efficiency, reasoning, and deployment now matter more than size
- DeepSeek-V3.2
- Z.ai GLM-4.7
- MiniMax-M2.1
- Xiaomi: MiMo-V2-Flash
✨ Multimodal reasoning is now default
- Z.ai GLM-4.6V
- Z.ai AutoGLM-Phone 9B
- Bytedance: Dolphin-v2
✨ Image & video: editable assets and real workflows
- Qwen-Image-Layered / Image-2512
- Meituan: LongCat-Image & Image Edit
- AIDC: Ovis-Image-7B
- Live-Avatar / LongCat-Video-Avatar
- HY-WorldPlay / RealVideo
✨ Audio goes edge ready
- GLM-ASR-Nano / Fun-ASR-Nano
- GLM-TTS / VoxCPM1.5
- CosyVoice 0.5B
✨ The quiet backbone: data & infrastructure
- Finch (FinWorkBench)
- Tencent ARC: TimeLens-100K
- BIGAI: TongSIM-Asset
- MiniMax: VTP-Base
✨ Also congrats on Minimax and Z.ai announced their IPOs and Moonshot announced a new $500M funding round 🔥
Like everyone else, I was OOO at the end of December, so feel free to share (in comments or PR) any I missed in this list!
liked a
model 7 months ago
colab notebook link to test the model
2
#6 opened 7 months ago
by moon005
liked a
model 7 months ago
colab / kaggle
1
#5 opened 7 months ago
by moon005
if your getting very blurry outputs
10
#2 opened 7 months ago
by 
realrebelai
reacted to mahimairaja's post with 🚀 7 months ago
Post
4798
Happy New Years 2026!
For next 365 days I will be commit to work on:
- Document AI and OCR Automations
- Voice Agents
- Long Running Tasks - Durable Agents
For next 365 days I will be commit to work on:
- Document AI and OCR Automations
- Voice Agents
- Long Running Tasks - Durable Agents
- 1 reply
reacted to projectlosangeles's post with ❤️ 7 months ago
Post
2143
🔥Project Los Angeles is proud to announce the release of midisim 🔥
midisim is a SOTA Python package for calculating, searching and analyzing MIDI-to-MIDI similarity at speed and scale!
projectlosangeles/midisim
projectlosangeles/midisim-embeddings
projectlosangeles/midisim-samples
If you like midisim, please ❤️
Project Los Angeles
Tegridy Code 2025
midisim is a SOTA Python package for calculating, searching and analyzing MIDI-to-MIDI similarity at speed and scale!
projectlosangeles/midisim
projectlosangeles/midisim-embeddings
projectlosangeles/midisim-samples
If you like midisim, please ❤️
Project Los Angeles
Tegridy Code 2025
llama cpp
🔥 4
3
#8 opened 7 months ago
by moon005
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