gemma-2b-grpo-500 – AI Model by heissanjay | AlphaNeural AI

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gemma-2b-grpo-500

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Gemma 2 2B RaR+GRPO Reasoning Model

Model Description

This model was fine-tuned using GRPO with Rubrics as Rewards (RaR) to produce structured reasoning traces.

Loading Instructions

python

from orbax import checkpoint as ocp
from flax import nnx

# Load LoRA parameters
checkpointer = ocp.StandardCheckpointer()
lora_params = checkpointer.restore("lora_params", target=abs_lora_state)

# Apply to base Gemma model
nnx.update(lora_policy, lora_params)

Configuration

Base model: gemma2-2b-it
LoRA rank: 64
LoRA alpha: 128
Training samples: 500
Training steps: 112

Output Format

<reasoning>
Step-by-step thinking process
</reasoning>
<answer>
Final answer
</answer>