Instructions to use adimyth/compass-lora-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use adimyth/compass-lora-v2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.5-4B") model = PeftModel.from_pretrained(base_model, "adimyth/compass-lora-v2") - Notebooks
- Google Colab
- Kaggle
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Download README.md from adimyth/compass-lora-v2: direct link, hf CLI and curl.
- Browser
- Download file 597 Bytes
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https://huggingface.co/adimyth/compass-lora-v2/resolve/main/README.md
- Command line
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hf download hf://adimyth/compass-lora-v2/README.md
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curl -L -o README.md https://huggingface.co/adimyth/compass-lora-v2/resolve/main/README.md
597 Bytes
| base_model: Qwen/Qwen3.5-4B | |
| library_name: peft | |
| license: apache-2.0 | |
| tags: [lora, decision-model, compass] | |
| LoRA adapter for [Compass](https://github.com/adimyth/compass) `compass-0.2.0`: rank 16 on the attention and MLP projections of Qwen3.5-4B (revision `851bf6e8`), trained through Compass's verification and direct readouts on its own generated and drafted decision items. Load it through the Compass server (`scripts/serve.sh`), which merges it at start; `calibration.json` holds the matching per-type temperatures. Results and method: the repository README and `docs/EXPERIMENTS.md`. | |