Search Results for "expert system source code" - Page 21
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Showing 505 open source projects for "expert system source code"
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Smaug Flash
304B MoE model optimized for agentic coding and long-running workflows
Smaug Flash is an open-weight agentic coding model from Abacus.AI, fine-tuned from DeepSeek-V4-Flash-0731 to improve autonomous software engineering, tool use, and long-running agent workflows. It uses a 304B-parameter Mixture-of-Experts architecture with 43 layers, 256 routed experts, six selected experts per token, and one shared expert. Its attention system combines Multi-Head Latent Attention with a sparse token indexer, while DSpark multi-token prediction provides speculative decoding... -
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Green Tara's OO jDREW
Mirror of Green Tara's OO jDREW fork on Bitbucket
This is a mirror site for downloads and forks. There is no documentation or issue tracking here. Please see the code issue tracking system on Bitbucket at https://bitbucket.org/taraathan/oojdrew -
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LocalLLM Studio
Chat with local GGUF LLMs on your own machine
...localllm-studio 1.0.5 v1.0.5 Aug 20, 2026 Windows: double-click the -Setup.exe to install. Authenticode-signed with the Dosvak LLC EV code-signing certificate (Sectigo Public Code Signi Built entirely by AI. Source: https://github.com/quickpod/localllm-studio -
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SCULT-TOOLS
15 free tools, 1000+ prompt, Skills for People No signup, no limits.
Scult Tools is a set of 15 free web tools that run entirely in your browser — schema markup generator, invoice generator, QR codes with UPI, JSON formatter, website speed test, ROI calculator, colour palette + WCAG contrast checker, word counter, business name and slogan generators, email signatures, favicons, UTM builder, FAQ schema, and an AI Visibility Checker that tells you whether ChatGPT knows your brand exists. Built for marketers, SEOs, freelancers and developers who just... -
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Qwable-v1
Agentic coding model combining Opus reasoning and Fable tools
Qwable-v1 is an open-weight agentic coding model created through a chained distillation process based on Qwen3.6-35B-A3B. The model combines two distinct training stages: first, it was fine-tuned on reasoning traces derived from Claude Opus 4.7 to improve structured reasoning, and then further trained on Claude Fable-5 agentic tool-use traces to develop autonomous coding and tool-calling behavior. The result is a 35B Mixture-of-Experts model with only 3B active parameters that can switch...
