README.md

metadata

title: ENIAD AI Assistant Chat
emoji: 🎓
colorFrom: purple
colorTo: blue
sdk: gradio
app_file: app.py
pinned: true
short_description: Interactive ENIAD AI Assistant (LLaMA-3.1-8B)

🎓 ENIAD Assistant — Live Interactive Space

🤝 Official Multi-Author Engineering Project • ENIAD AI Lab (May 2025)

Welcome to the interactive conversational interface for ENIAD-ASSISTANT, powered by a fine-tuned LLaMA-3.1-8B model.

👥 Engineering Team

• Abdellah ENNAJARI — Lead AI & MLOps Engineer (@abdennajari • GitHub @ennajari)
• Ahmed OUKACHA — AI Systems & Fine-Tuning Specialist (@ahmed-ouka)
• Oussama EL HADJI — Full-Stack AI UI & SMA Multi-Agent Engineer (HF @bosaj • GitHub @Bosaj)
• Abdelilah OURTI (@abdelilahou) — Vector DB & RAG Pipeline Engineer

🔗 Architecture & Associated Assets

• Original Model Checkpoint (May 2025): ahmed-ouka/my-llama3.1-8B-with-lora-Eniad-Assistant
• Official Model Card: bosaj/eniad-llama3.1-8b-assistant-lora
• Instruction Dataset: bosaj/eniad-assistant-instruct-dataset
• GitHub Repository: ennajari/ENIAD-ASSISTANT

🏛️ The Complete ENIAD Chatbot Model Family (LLaMA & Qwen)

The ENIAD Chatbot ecosystem consists of collaborative LLaMA & Qwen checkpoints, quantization profiles, and LoRA adapters engineered for our institutional assistant:

Model & Checkpoint	Base Architecture	Precision / Format	Target Environment & Use-Case	Verified Repository Link
LLaMA-3.1-8B Assistant LoRA	meta-llama/Llama-3.1-8B	16-Bit PEFT LoRA (Rank 16, Alpha 32)	Primary institutional conversational assistant (Bilingual FR/EN)	bosaj/eniad-llama3.1-8b-assistant-lora
LLaMA-3-8B Merged 32-Bit	meta-llama/Meta-Llama-3-8B	Full Float32 Merged Weights	Standalone backend inference server without runtime adapter loading	ahmed-ouka/llama3-8b-eniad-merged-32bit
LLaMA-3.1-8B Team Milestone	meta-llama/Llama-3.1-8B	PEFT LoRA Sharded Safetensors	Original PFA milestone model checkpoint (May 2025 team release)	ahmed-ouka/my-llama3.1-8B-with-lora-Eniad-Assistant
Eniad LLaMA 8-Bit Quantized	meta-llama/Meta-Llama-3-8B	8-Bit bitsandbytes NF4/INT8	High-efficiency local inference on edge GPUs (< 6GB VRAM)	ahmed-ouka/Eniad-model-llama-Assistant
LLaMA-Factory 3.1 LoRA Adapter	meta-llama/Llama-3.1-8B	Modular PEFT Adapter (~50MB)	Exported modular weights from the LLaMA-Factory training pipeline	ahmed-ouka/llama-lora-adapter-eniad
Qwen-2.5-1.5B ENIAD LoRA	Qwen/Qwen2.5-1.5B-Instruct	16-Bit PEFT LoRA (Compact)	Ultra-fast lightweight assistant for low-latency & edge devices (< 2GB VRAM)	ahmed-ouka/lora-qwen-eniad

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