Instructions to use ZHEN-04/Scaling-RL-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZHEN-04/Scaling-RL-4B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ZHEN-04/Scaling-RL-4B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Scaling-RL: Qwen3-4B RL checkpoints
Checkpoint backup. Qwen3-4B-Base trained with GRPO / PPO / DAPO, each under three rollout schedules (Sync / Tail / Sorted): 3 x 3 x 3 core runs plus single-seed variants.
Run matrix (4B)
- 27 core runs: 3 algorithms x 3 schedules x 3 seeds (
s1,s2,s3); 2K response cap, 8 responses per prompt, 128 prompts per update, 100 updates; checkpoints at updates 50 and 100. - 54 sweep runs: 3 algorithms x 3 schedules x 6 variants, one seed, 50 updates; checkpoint at update 50.
len1k/len4k(response cap 1K / 4K),n4/n16(responses per prompt),p64/p256(prompts per update). - Planned: same matrix and settings as 0.6B/1.7B. No checkpoints yet.
License
Not open for download at this time; access requests are not being approved.
Model tree for ZHEN-04/Scaling-RL-4B
Base model
Qwen/Qwen3-4B-Base