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tomyimkc/sophia-agi-lora-v1
sophia-agi-lora-v1 is a machine learning model from tomyimkc. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
Wisdom before intelligence. LoRA adapter for provenance-aware instruction on Qwen/Qwen2.5-3B-Instruct.
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Updated Jun 18, 2026
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From the Hugging Face model README
Wisdom before intelligence. LoRA adapter for provenance-aware instruction on Qwen/Qwen2.5-3B-Instruct.
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
base = "Qwen/Qwen2.5-3B-Instruct"
adapter = "tomyimkc/sophia-agi-lora-v1"
tokenizer = AutoTokenizer.from_pretrained(adapter)
model = AutoModelForCausalLM.from_pretrained(base, device_map="auto", torch_dtype="auto")
model = PeftModel.from_pretrained(model, adapter)
Train locally:
pip install -r requirements-lora.txt
python tools/prepare_lora_dataset.py
python tools/train_lora.py --4bit --epochs 3
Evaluate:
python tools/eval_local_model.py --adapter training/lora/checkpoints/sophia-v1 --with-gate
Ollama:
ollama create sophia-7b -f models/ollama/Modelfile
sophia_gate_check (MCP) or agent/gate.py — weights alone do not guarantee trap safety.