Open-MOPD-SmolLM3-3B-RL-Code

Open-MOPD-SmolLM3-3B-RL-Code

This is the code-domain teacher in the Open-MOPD pipeline. It starts from BytedTsinghua-SIA/Open-MOPD-SmolLM3-3B-MixSFT and is trained only on code prompts with verifiable rewards using GRPO. This release corresponds to training step 180.

Training uses global batch size 128, mini-batch size 32, learning rate 1e-6, rollout group size 16, a 30,000-token response limit, no KL penalty, and accuracy-based group filtering.

Results

Results use avg@10 rather than best@10, with temperature 1.0, max_model_len=32768, top_p=0.95, top_k=-1, and stop_token_ids=[128012].

The code portion of the RL prompt mixture explicitly excludes LiveCodeBench. The decontamination record is available in BytedTsinghua-SIA/Open-MOPD-Data under rl_prompt_mix/manifest.json.

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "BytedTsinghua-SIA/Open-MOPD-SmolLM3-3B-RL-Code"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, dtype="bfloat16", device_map="auto")

Intended use and limitations

This is a domain teacher intended for distillation, not a general-purpose assistant. It was optimized only on code and can perform worse than MixSFT on other domains.

Model specifications

• Architecture: SmolLM3ForCausalLM
• Parameters: approximately 3B
• Layers: 36
• Vocabulary size: 128,256
• Weights: BF16, approximately 6.2 GB
• Includes tokenizer and chat template