Text Generation
PEFT
Safetensors
English
thox
router
routing
preference-routing
qwen2
lora
conversational
Instructions to use Thox-ai/ThoxRoute-1.5B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Thox-ai/ThoxRoute-1.5B with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-1.5B-Instruct") model = PeftModel.from_pretrained(base_model, "Thox-ai/ThoxRoute-1.5B") - Notebooks
- Google Colab
- Kaggle
ThoxRoute-1.5B
Your AI. Your Data. Your Rules.
Preference-routing LoRA adapter on Qwen2.5-1.5B-Instruct — a clean-room router (built to avoid the non-commercial Arch-Router license).
What this is
- Base: Qwen/Qwen2.5-1.5B-Instruct (Apache-2.0).
- LoRA r=16, α=32; task = preference/intent routing.
- Clean-room implementation — explicitly not derived from katanemo/Arch-Router (non-commercial).
Intended use
On-device / edge text generation within the THOX stack. Not a safety-aligned public assistant unless deployed behind THOX guardrails.
Prompt / chat template
<|im_start|>system
{system}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
Usage
Transformers + PEFT
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
base = "Qwen/Qwen2.5-1.5B-Instruct"
adapter = "Thox-ai/ThoxRoute-1.5B"
tok = AutoTokenizer.from_pretrained(base)
model = AutoModelForCausalLM.from_pretrained(base, device_map="auto")
model = PeftModel.from_pretrained(model, adapter)
Links
- Base model:
Qwen/Qwen2.5-1.5B-Instruct - GGUF:
Thox-ai/ThoxRoute-1.5B-GGUF - Ollama:
ollama.com/thox-ai/<slug>— verify with the Ollama lane (task 80017303) - Docs: https://docs.thox.ai
THOX.ai LLC — Your AI. Your Data. Your Rules. · On-device and private by design.
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