Contributing to the Chinese ML community.
huggingface.co/baidu/ERNIE-...
✨ Small MoE - Apache 2.0
✨ 128K context length for deep reasoning
✨ Efficient tool usage capabilities
huggingface.co/baidu/ERNIE-...
✨ Small MoE - Apache 2.0
✨ 128K context length for deep reasoning
✨ Efficient tool usage capabilities
huggingface.co/baidu/ERNIE-...
✨ Small MoE - Apache 2.0
✨ 128K context length for deep reasoning
✨ Efficient tool usage capabilities
huggingface.co/baidu/ERNIE-...
✨ Small MoE - Apache 2.0
✨ 128K context length for deep reasoning
✨ Efficient tool usage capabilities
huggingface.co/openbmb/Mini...
✨ 8B - Apache 2.0
✨ Hybrid reasoning model: deep reasoning +fast inference.
✨5x faster on edge chips, 90% smaller (BitCPM)
✨Trained on UltraClean + UltraChat v2 data
huggingface.co/openbmb/Mini...
✨ 8B - Apache 2.0
✨ Hybrid reasoning model: deep reasoning +fast inference.
✨5x faster on edge chips, 90% smaller (BitCPM)
✨Trained on UltraClean + UltraChat v2 data
huggingface.co/datasets/m-a...
huggingface.co/papers/2509....
Testing LLMs on their ability to override biases & follow adversarial instructions.
✨ 8 challenge types
✨ 1,012 CN/EN Qs across 23 domains
✨ Human-in-the-loop + LLM-as-a-Judge
huggingface.co/datasets/m-a...
huggingface.co/papers/2509....
Testing LLMs on their ability to override biases & follow adversarial instructions.
✨ 8 challenge types
✨ 1,012 CN/EN Qs across 23 domains
✨ Human-in-the-loop + LLM-as-a-Judge
huggingface.co/collections/...
✨ 46B total / 2.5B active - Apache2.0
✨ Dense-level performance at lower cost
✨ Trained on 22T tokens with progressive curriculum
✨ 64K context length
huggingface.co/collections/...
✨ 46B total / 2.5B active - Apache2.0
✨ Dense-level performance at lower cost
✨ Trained on 22T tokens with progressive curriculum
✨ 64K context length
Kimi K2 >>> Kimi K2-Instruct-0905🔥
huggingface.co/moonshotai/K...
✨ 32B activated / 1T total parameters
✨ Enhanced agentic coding intelligence
✨ Better frontend coding experience
✨ 256K context window for long horizon tasks
Kimi K2 >>> Kimi K2-Instruct-0905🔥
huggingface.co/moonshotai/K...
✨ 32B activated / 1T total parameters
✨ Enhanced agentic coding intelligence
✨ Better frontend coding experience
✨ 256K context window for long horizon tasks
huggingface.co/meituan-long...
huggingface.co/meituan-long...
Demo
huggingface.co/spaces/byted...
Model
huggingface.co/bytedance-re...
Paper
huggingface.co/papers/2508....
Demo
huggingface.co/spaces/byted...
Model
huggingface.co/bytedance-re...
Paper
huggingface.co/papers/2508....
huggingface.co/collections/...
huggingface.co/collections/...
huggingface.co/spaces/zh-ai...
✨Goal: By 2035, AI will deeply empower all sectors, reshape productivity & society
✨Focus on 6 pillars:
>Science & Tech
>Industry
>Consumption
>Public welfare
>Governance
>Global cooperation
huggingface.co/spaces/zh-ai...
✨Goal: By 2035, AI will deeply empower all sectors, reshape productivity & society
✨Focus on 6 pillars:
>Science & Tech
>Industry
>Consumption
>Public welfare
>Governance
>Global cooperation
huggingface.co/openbmb/Mini...
huggingface.co/openbmb/Mini...
huggingface.co/collections/...
✨ 1B · 2B · 4B · 8B · 14B · 38B | MoE → 20B-A4B · 30B-A3B · 241B-A28B 📄Apache 2.0
✨ +16% reasoning performance, 4.05× speedup vs InternVL3
huggingface.co/collections/...
✨ 1B · 2B · 4B · 8B · 14B · 38B | MoE → 20B-A4B · 30B-A3B · 241B-A28B 📄Apache 2.0
✨ +16% reasoning performance, 4.05× speedup vs InternVL3
huggingface.co/internlm/Int...
✨ Efficient 8B LLM + 0.3B vision encoder
✨ Apache 2.0
✨ 5T multimodal pretraining, 50%+ in scientific domains
✨ Dynamic tokenizer for molecules & protein sequences
huggingface.co/internlm/Int...
✨ Efficient 8B LLM + 0.3B vision encoder
✨ Apache 2.0
✨ 5T multimodal pretraining, 50%+ in scientific domains
✨ Dynamic tokenizer for molecules & protein sequences
huggingface.co/collections/...
✨ 36B - Base & Instruct
✨ Apache 2.0
✨ Native 512K long context
✨ Strong reasoning & agentic intelligence
✨ 2 Base versions: with & without synthetic data
huggingface.co/collections/...
✨ 36B - Base & Instruct
✨ Apache 2.0
✨ Native 512K long context
✨ Strong reasoning & agentic intelligence
✨ 2 Base versions: with & without synthetic data
When I came back: Qwen still releasing
Respect!!🫡
Qwen Image Edit 🔥 the image editing version of Qwen-Image by Alibaba Qwen
huggingface.co/Qwen/Qwen-Im...
When I came back: Qwen still releasing
Respect!!🫡
Qwen Image Edit 🔥 the image editing version of Qwen-Image by Alibaba Qwen
huggingface.co/Qwen/Qwen-Im...
huggingface.co/collections/...
I’ve been tracking things closely, but July’s open-source wave still managed to surprise me.
Can’t wait to see what’s coming next! 🚀
huggingface.co/collections/...
I’ve been tracking things closely, but July’s open-source wave still managed to surprise me.
Can’t wait to see what’s coming next! 🚀
They just released Qwen3-Coder-30B-A3B-Instruct on the hub
huggingface.co/Qwen/Qwen3-C...
✨ Apache 2.0
✨30B total / 3.3B active (128 experts, 8 top-k)
✨ Native 256K context, extendable to 1M via Yarn
✨ Built for Agentic Coding
They just released Qwen3-Coder-30B-A3B-Instruct on the hub
huggingface.co/Qwen/Qwen3-C...
✨ Apache 2.0
✨30B total / 3.3B active (128 experts, 8 top-k)
✨ Native 256K context, extendable to 1M via Yarn
✨ Built for Agentic Coding
Model: huggingface.co/stepfun-ai/s...
Paper: huggingface.co/papers/2507....
Model: huggingface.co/stepfun-ai/s...
Paper: huggingface.co/papers/2507....
huggingface.co/Qwen/Qwen3-3...
✨ 30B total / 3B active - Apache 2.0
✨ Native 256K context
✨ SOTA coding, alignment, agentic reasoning
huggingface.co/Qwen/Qwen3-3...
✨ 30B total / 3B active - Apache 2.0
✨ Native 256K context
✨ SOTA coding, alignment, agentic reasoning
huggingface.co/collections/...
✨ 1.5 B - MIT License
✨ Runs on RTX 4090
✨ Truly unified architecture
huggingface.co/collections/...
✨ 1.5 B - MIT License
✨ Runs on RTX 4090
✨ Truly unified architecture
huggingface.co/Qwen/Qwen3-3...
✨ 30B MoE / 3.3B active - Apache 2.0
✨ Strong gains in reasoning, math, coding, & multilingual tasks
✨ Native support for 256K long-context inputs
huggingface.co/Qwen/Qwen3-3...
✨ 30B MoE / 3.3B active - Apache 2.0
✨ Strong gains in reasoning, math, coding, & multilingual tasks
✨ Native support for 256K long-context inputs
huggingface.co/Wan-AI/Wan2....
huggingface.co/Wan-AI/Wan2....
huggingface.co/Wan-AI/Wan2....
huggingface.co/Wan-AI/Wan2....
Built for intelligent agents with unified capabilities: reasoning, coding, tool use.
huggingface.co/collections/...
✨ 355B total / 32B active - MIT license
✨ Hybrid modes: Thinking mode for complex tasks/ Non-thinking mode for instant replies
Built for intelligent agents with unified capabilities: reasoning, coding, tool use.
huggingface.co/collections/...
✨ 355B total / 32B active - MIT license
✨ Hybrid modes: Thinking mode for complex tasks/ Non-thinking mode for instant replies