Chess-RL-Models

RL (GRPO) post-training checkpoint trajectories for the chess pre-to-post compute-allocation study. Companion to Chess-Pretrain-Models (pretraining bases) and Chess-SFT-Models (SFT initialisations). Model names match across all three repos, so model_50m_17B here is the RL run started from model_50m_17B there.

28 models, 680 checkpoints. Steps kept: every step ≡ 0 mod 100, plus each run's final step.

Layout

model_{size}_{pretraining_tokens}/
└── global_step_{N}/
    ├── config.json
    ├── model.safetensors
    ├── tokenizer.py      # custom tokenizer -> trust_remote_code=True
    ├── vocab.json
    └── ...

Loading

The remote-code resolver ignores subfolder=, so download the step folder and load the local path (each step folder is self-contained):

from huggingface_hub import snapshot_download
from transformers import AutoModelForCausalLM, AutoTokenizer

name, step = "model_50m_17B", "global_step_2000"
p = snapshot_download("Pre2Post-Chess-RL/Chess-RL-Models", allow_patterns=f"{name}/{step}/*") + f"/{name}/{step}"
model = AutoModelForCausalLM.from_pretrained(p, trust_remote_code=True)
tok = AutoTokenizer.from_pretrained(p, trust_remote_code=True)

Models

model	size	pretrain tokens	ckpts	steps
model_200m_0.27B	200m	0.267B	10	100–1000
model_200m_1.1B	200m	1.07B	20	100–2000
model_200m_2.1B	200m	2.13B	20	100–2000
model_200m_4.0B	200m	4B	10	100–1000
model_200m_5.3B	200m	5.33B	20	100–2000
model_20m_0.53B	20m	0.527B	20	100–2000
model_20m_1.6B	20m	1.58B	50	100–5000
model_20m_2.6B	20m	2.64B	49	100–4900
model_20m_5.3B	20m	5.27B	50	100–5000
model_20m_11B	20m	10.5B	50	100–5000
model_20m_16B	20m	15.8B	30	100–3000
model_20m_21B	20m	21.1B	50	100–5000
model_20m_32B	20m	31.6B	50	100–5000
model_20m_40B	20m	39.6B	49	100–4900
model_20m_53B	20m	52.7B	32	100–5000
model_50m_0.23B	50m	0.229B	20	100–2000
model_50m_0.69B	50m	0.687B	12	100–1200
model_50m_1.1B	50m	1.15B	10	100–1000
model_50m_2.3B	50m	2.29B	20	100–2000
model_50m_4.6B	50m	4.58B	20	100–2000
model_50m_9.2B	50m	9.16B	20	100–2000
model_50m_17B	50m	17.2B	20	100–2000
model_50m_23B	50m	22.9B	10	100–1000
model_50m_41B	50m	41.2B	18	100–2000
model_680m_0.32B	680m	0.319B	5	100–500
model_680m_1.6B	680m	1.6B	1	2000
model_680m_6.4B	680m	6.4B	10	100–1000
model_680m_16B	680m	16B	4	1200–1900

Not included

These models exist in the study but had no usable weights available at upload time:

• model_200m_0.53B
• model_200m_11B
• model_200m_21B
• model_200m_40B
• model_200m_53B
• model_680m_0.64B
• model_680m_1.2B
• model_680m_12B
• model_680m_3.2B
• model_680m_32B
• 2 32m models absent from the pretraining-token tables