Instructions to use rjz123/colar-logic-r1q with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use rjz123/colar-logic-r1q with PEFT:
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- Notebooks
- Google Colab
- Kaggle
colar-r1-logic
R1 warm-start ProsQA+FOLIO+LogiQA, comp5, mse, 25ep(้ ๆนๅ็ฆป)
- Base model:
deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B - Files:
colar_r1_logic.ckpt,hparams.yaml
Loading (PyTorch-Lightning checkpoint โ NOT AutoModel-loadable)
Weights live under the top-level key ['state_dict'] and only fit the custom CoLaR scaffold (base LLM + [PAD] resize + r128 q/v LoRA + a LatentPolicy MLP), loaded strict=False. Load the base separately and splice this state_dict in. Runtime env:
COLAR_BASE=<base> COLAR_CKPT=colar-gsm/colar_best.ckpt COLAR_EMB_STD=0.018 COLAR_COMPRESS=5 COLAR_MAXLAT=64 TORCH_FORCE_NO_WEIGHTS_ONLY_LOAD=1
TORCH_FORCE_NO_WEIGHTS_ONLY_LOAD=1 is required for these older Lightning ckpts.
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Base model
deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B