Kwaipilot/KAT-Coder-V2.5-Dev
Text Generation • 35B • Updated • 5.31k • 229
Maksym Sorokin
Linukso1D
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reacted to danielhanchen's post with 🚀 8 days ago
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Gemma 4 is now faster and much more accurate! 🚀
Google made huge improvements to tool-calling and chat accuracy, reliability + speed.
To get fixes, re-download our updated GGUF, MLX, NVFP4 quants!
Unsloth quants: https://huggingface.co/collections/unsloth/gemma-4
Gemma 4 Guide: https://unsloth.ai/docs/models/gemma-4
Google made huge improvements to tool-calling and chat accuracy, reliability + speed.
To get fixes, re-download our updated GGUF, MLX, NVFP4 quants!
Unsloth quants: https://huggingface.co/collections/unsloth/gemma-4
Gemma 4 Guide: https://unsloth.ai/docs/models/gemma-4
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#3 opened about 1 month ago
by Linukso1D
failed to parse grammar with llama.cpp on master
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#4 opened about 1 month ago
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nervousapps
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reacted to sequelbox's post with ❤️ 3 months ago
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JUST RELEASED: the Tachibana 4 DeepSeek-V4-Pro dataset and our all-new Tachibana-Agent coding model!
- Questions prioritize real-world, challenging agentic coding tasks across a variety of programming languages and topics. Synthetic prompts utilize a variety of personas, experience levels, and styles of communication to maximize real-world flexibility and usability.
- Areas of focus include back-end and front-end development, systems programming, distributed systems, performance optimization, data structures, databases and data engineering, game and mobile development, security engineering, compiler design, custom tooling, task automation, practical bugfixes, and more!
- A wide variety of emphasized languages improves development capability: Python, C, C++, C#, Go, TypeScript, Java, JavaScript, Rust, Haskell, SQL, Shell, R, Ruby, assembly code, and more!
The new dataset: sequelbox/Tachibana4-DeepSeek-V4-Pro
The new model: sequelbox/Qwen3.6-27B-Tachibana-Agent
We're thrilled to bring this to everyone - try it out and see what you think!
Tachibana 4 is the first of several datasets used for the upcoming Esper 4! See what we're working on and help our releases come out faster: sequelbox/SupportOpenSource
Open source will win :)
love,
allegra
- Questions prioritize real-world, challenging agentic coding tasks across a variety of programming languages and topics. Synthetic prompts utilize a variety of personas, experience levels, and styles of communication to maximize real-world flexibility and usability.
- Areas of focus include back-end and front-end development, systems programming, distributed systems, performance optimization, data structures, databases and data engineering, game and mobile development, security engineering, compiler design, custom tooling, task automation, practical bugfixes, and more!
- A wide variety of emphasized languages improves development capability: Python, C, C++, C#, Go, TypeScript, Java, JavaScript, Rust, Haskell, SQL, Shell, R, Ruby, assembly code, and more!
The new dataset: sequelbox/Tachibana4-DeepSeek-V4-Pro
The new model: sequelbox/Qwen3.6-27B-Tachibana-Agent
We're thrilled to bring this to everyone - try it out and see what you think!
Tachibana 4 is the first of several datasets used for the upcoming Esper 4! See what we're working on and help our releases come out faster: sequelbox/SupportOpenSource
Open source will win :)
love,
allegra
reacted to danielhanchen's post with 🔥 3 months ago
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We made a guide on how to run open LLMs in Claude Code, Codex and OpenClaw.
Use Gemma 4 and Qwen3.6 GGUFs for local agentic coding on 24GB RAM
Run with self-healing tool calls, code execution, web search via the Unsloth API endpoint and llama.cpp
Guide: https://unsloth.ai/docs/basics/api
Use Gemma 4 and Qwen3.6 GGUFs for local agentic coding on 24GB RAM
Run with self-healing tool calls, code execution, web search via the Unsloth API endpoint and llama.cpp
Guide: https://unsloth.ai/docs/basics/api