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README.md
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## Alpha Intelligence. Download your AIs
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* *MoE models for best speed vs quality on the laptop*
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* Choose 4bit - 6bit versions for efficiency.
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* **Supported by now:**
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* **Qwen3.6** (very good quality)
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- [unsloth/Qwen3.6-35B-A3B-MTP-GGUF](https://huggingface.co/unsloth/Qwen3.6-35B-A3B-MTP-GGUF/tree/main) — recommended
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- [unsloth/gemma-4-26B-A4B-it-GGUF](https://huggingface.co/unsloth/gemma-4-26B-A4B-it-GGUF/tree/main) — efficient
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- [unsloth/google_gemma-4-e2b-it-GGUF](https://huggingface.co/unsloth/gemma-4-E2B-it-GGUF/tree/main) — fast debug cycles
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- [unsloth/google_gemma-4-e4b-it-GGUF](https://huggingface.co/unsloth/gemma-4-E4B-it-GGUF/tree/main) — balanced
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*The `ai/` folder is excluded from git. GGUFs are never committed to this repository.*
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## Alpha Intelligence. Download your AIs
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* *MoE models for best speed vs quality on the laptop*
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* **Supported by now:**
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* **Qwen3.6** (very good quality)
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* **Gemma-4** (concise think mode)
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* Choose 4bit - 6bit versions for efficiency.
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1. Download the GGUF files from Hugging Face. **Download links recommendation:**
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* [MoT AI: unsloth/Qwen3.6-35B-A3B-MTP-GGUF](https://huggingface.co/unsloth/Qwen3.6-35B-A3B-MTP-GGUF/tree/main) — recommended
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* [MoT AI: unsloth/gemma-4-26B-A4B-it-GGUF](https://huggingface.co/unsloth/gemma-4-26B-A4B-it-GGUF/tree/main) — efficient
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* [Dense AI: unsloth/gemma-4-e2b-it-GGUF](https://huggingface.co/unsloth/gemma-4-E2B-it-GGUF/tree/main) — fast debug cycles
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* [Dense AI: unsloth/gemma-4-e4b-it-GGUF](https://huggingface.co/unsloth/gemma-4-E4B-it-GGUF/tree/main) — balanced
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2. Place them in the `ai/` folder inside the repo.
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3. Then copy the GGUF ai name and paste it in the config.py under `_ALPHA_INTELLIGENCE_TO_LOAD` and choose `_MODEL_TYPE: "qwen" OR "gemma"`**
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*The `ai/` folder is excluded from git. GGUFs are never committed to this repository.*
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