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🔄 In a Training Loop

Loom

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Independent builder training small/efficient models from scratch on consumer hardware.

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upvoted a changelog about 2 hours ago
A New Main Search UI
reacted to Quazim0t0's post with 🔥 1 day ago
https://huggingface.co/Quazim0t0/Qwenx86-4B-compact ▶️ See it in action: https://huggingface.co/spaces/Quazim0t0/Qwenx86-Debugger . Walk through actual recorded tool calls: the conversation, x86 registers and flags, code at the program counter, RAM and machine output, with all verified blocks on a timeline. Qwen3.5-4B with a 64-bit x86 computer compiled into its weights: 13 transformer layers ahead of Qwen's own. There are no learned weights in them; all of their weights are computed by a compiler. Qwen invokes the computer through its own tool calls (<tool_call>), and the computer in the weights executes the tool. Calculator, Python, C compiler, notes store, physics/chemistry lookup and Python-docs lookup are all firmware in the checkpoint. This is the compact checkpoint: ~9 GB GPU memory, so it fits on a 16 GB GPU. Edit: GGUF Release: https://huggingface.co/Quazim0t0/Qwenx86-4B-GGUF Credits: Qwenputer by Divyansh Agrawal (@divagr1925, github.com/divagr18/qwenputer, MIT)
reacted to SeaWolf-AI's post with 🔥 1 day ago
SuperCLUE’s November 2026 results highlight why category scores matter when choosing a model. Across the 19 published entries, here are the highest displayed scores in each category, followed by the leader among models labeled open: • Agentic coding: GPT-6.1-Sol (69.23); open: DeepSeek-V4.1-Flash-1017 (65.38). • Mathematical and scientific reasoning: GPT-6.1-Sol (76.32); open: Darwin-180B-RSI-R3 (73.68). • Hallucination control: Gemini-4-Argon (83.19); open: Kimi-K3.1-Pro (67.78). • Precise instruction following: Gemini-4-Argon and GPT-6.1-Sol (68.97 each); open: Kimi-K3.1-Pro (44.83). • Ultra-long context: Gemini-4-Argon (95.63); open: Kimi-K3.1-Pro (87.25). On the overall leaderboard, Gemini-4-Argon (73.62) and GPT-6.1-Sol (71.76) have the highest displayed scores, but neither has an official rank number. Kimi-K3.1-Pro (61.46) holds official rank No. 1 and leads the open models overall, followed by DeepSeek-V4.1-Flash-1017 (58.95, official No. 2) and GLM-5.3 (50.66, official No. 3). These comparisons include entries whose official rank is “-”. Among officially ranked open models only, DeepSeek leads mathematical and scientific reasoning at 71.05. “Open” follows SuperCLUE’s classification, not an independent license review. Scores are benchmark points, not error rates; small differences and results from a Chinese-language-focused evaluation need validation on your own workloads. Detailed evaluation settings and the aggregation formula were not verified for this summary. Read the full breakdown: https://huggingface.co/blog/FINAL-Bench/superclue-november-2026-category-leaders-open-mode Source: SuperCLUE results released November 5, 2026 https://www.superclueai.com/homepage Official November data: https://www.superclueai.com/data/generalboard/2026%E5%B9%B411%E6%9C%88.xlsx
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