Anthropic/enabling-independent-research
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👋 Open to Work
perk bevis
perkbevis
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AI & ML interests
Exploring open-source AI/ML models and learning how to integrate smart AI features into modern applications.
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JonathanColetti/Qwen3.8-27B-Uncensored-GGUF
Text Generation • 27B • Updated • 2.99M • 1.1k
orcarouter/Qwen3.8-27B-Uncensored-GGUF
Image-Text-to-Text • 27B • Updated • 337k • 942
zai-org/GLM-5.3
Text Generation • 753B • Updated • 669k • • 1.82k
deepseek-ai/DeepSeek-V4-Flash-Vision-Exp
Image-Text-to-Text • 305B • Updated • 519k • • 893
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Hugging Face Changelog
Build Spaces with AI Agents
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Egress metrics for users and organizations
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Hugging Face Changelog
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it can code
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#1 opened 9 days ago
by 
Bc-AI
reacted to Banaxi-Tech's post with 🔥 23 days ago
Post
3791
We're announcing our BananaMind 2.1 model series!
The models will include:
- BananaMind 2.1 Nano: 10M parameters with 60B tokens.
- BananaMind 2.1 Lite: 25M parameters with 40B tokens.
- BananaMind 2.1 Flash: 50M parameters with 55B tokens.
- BananaMind 2.1 Pro: 135M-145M parameters (still deciding) with 100B tokens.
These model will use a multi tower architecture (like BananaMind/BananaMind-2.1-Unified) with some more architectural changes.
BananaMind 2.1 Pro will probrably use 2 no output towers, instead of one!
We're currently training some experimental models based on this architecture to see its scaling!
Follow us:
BananaMind
@Banaxi-Tech
@vovaRL
@DedeProGames
bananamind-research-community
The models will include:
- BananaMind 2.1 Nano: 10M parameters with 60B tokens.
- BananaMind 2.1 Lite: 25M parameters with 40B tokens.
- BananaMind 2.1 Flash: 50M parameters with 55B tokens.
- BananaMind 2.1 Pro: 135M-145M parameters (still deciding) with 100B tokens.
These model will use a multi tower architecture (like BananaMind/BananaMind-2.1-Unified) with some more architectural changes.
BananaMind 2.1 Pro will probrably use 2 no output towers, instead of one!
We're currently training some experimental models based on this architecture to see its scaling!
Follow us:
@Banaxi-Tech
@vovaRL
@DedeProGames
- 10 replies
reacted to onekq's post with 🤗 about 1 month ago
Post
2229
There has been a leaked memo (now struck down) from the founder of DeepSeek. I'm not here to circulate it, but comment on the minimum-effort evolutionary path he proposed.
LLM->CoT->Agent->Self-improvement->Singularity->Physical
This makes sense to me: even at the agent stage I learn world models much faster than when I learned LLM at the LLM stage.
But this means humans are still needed beyond the digital singularity, until robots can close their own loop: eval, manufacturing, self improvement, i.e. physical singularity.
LLM->CoT->Agent->Self-improvement->Singularity->Physical
This makes sense to me: even at the agent stage I learn world models much faster than when I learned LLM at the LLM stage.
But this means humans are still needed beyond the digital singularity, until robots can close their own loop: eval, manufacturing, self improvement, i.e. physical singularity.