๐๏ธ Architech โ CognoSphere Model Factory
Build, train, and deploy CSUMLM-class language models.
๐ก CPU mode โ smaller models available. Upgrade to GPU for Gemma 4 / Llama 3 / Mistral ๐ง LoRA/PEFT available โ parameter-efficient fine-tuning enabled
Powered by Or4cl3 AI Solutions โ CognoSphere Unified Multimodal Language Model (CSUMLM)
๐ Select Existing Dataset
CPU models: distilgpt2, TinyLlama, Qwen2.5. GPU required: Gemma 4, Llama 3, Mistral
Manage Your Models
Upload, download, and organize your trained models
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๐ฅ Download Model
๐ Local Models
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Generate Professional Model Card & Research Paper
๐ Model Information
๐ฅ Generated Documents
Click generate to create documentation
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๐๏ธ Architech โ CognoSphere Model Factory
Version: 2.0.0 By: Or4cl3 AI Solutions
What is Architech?
Architech is the model training and deployment platform for the CognoSphere Unified Multimodal Language Model (CSUMLM) ecosystem. It provides an end-to-end pipeline for:
- Synthetic Data Generation โ Domain-specific training data creation
- Model Training โ Fine-tuning with LoRA/QLoRA on modern base models
- Model Testing โ Interactive inference and evaluation
- Model Management โ Upload, download, and organize models
- Documentation โ Auto-generated model cards and research papers
- Repository Chat โ Manage your HuggingFace repos conversationally
Supported Base Models
| Model | Parameters | Hardware | Notes |
|---|---|---|---|
| distilgpt2 | 82M | CPU โ | Fast prototyping |
| GPT-2 | 124M | CPU โ | Classic baseline |
| TinyLlama 1.1B | 1.1B | CPU โ | Strong small model |
| Qwen2.5-0.5B | 500M | CPU โ | Efficient instruct model |
| Qwen2.5-1.5B | 1.5B | CPU โ | Good balance |
| Gemma 2 2B | 2B | CPU โ | Google's small model |
| Gemma 4 12B | 12B | GPU ๐ถ | Recommended for CSUMLM |
| Gemma 4 26B-A4B | 26B (4B active) | GPU ๐ถ | MoE โ top pick for CSUMLM |
| Llama 3.2 3B | 3B | GPU ๐ถ | Meta's compact model |
| Mistral 7B | 7B | GPU ๐ถ | Strong general model |
| Phi-3 Mini | 3.8B | GPU ๐ถ | Microsoft's efficient model |
CognoSphere / CSUMLM
CSUMLM integrates the CognoSphere Multimodal AI Engine (CSMAE) and the CognoSphere Large Language Model (CSLLM) into a unified system. Key components:
- Hybrid Learning Engine โ Transfer learning + meta-learning + LoRA
- I-RAGEL Framework โ Internal Retrieval Augmented Generation Enhanced Logic
- BDI/CoT Reasoning โ Belief-Desire-Intent / Chain of Thought structure
- ฮฃ-Matrix Governance โ SECA cognitive architecture constraints
- Dynamic Knowledge Base โ Continuously updated linguistic patterns
Status
๐ก CPU Mode โ Upgrade to HF Pro for GPU access ๐ข LoRA Available
ยฉ 2026 Or4cl3 AI Solutions โ Apache 2.0 License