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FlameF0X
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Model Details
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FlameF0X
Model Tree
FlameF0X/ChessSLM
Input Modalities
Output Modalities
Supported Functionality
ChessSLM demonstrates that specialized small language models can perform competitively in narrow domains such as chess.
ChessSLM can play chess by generating moves sequentially in SAN notation.
It has been evaluated in matches against several language models, including:
The model achieves an averaging rating of around {tba} Elo against other language models despite its small size.
| Model | Elo Rating |
|---|---|
| FlameF0X/ChessSLM | 1154 |
| DedeProGames/mini-chennus | 1114 |
| EleutherAI/pythia-70m-deduped | 1099 |
| nlpguy/smolchess-v2 | 1092 |
| DedeProGames/dialochess | 1078 |
| nlpguy/amdchess-v9 | 1073 |
| mlabonne/grandpythia-200k-70m | 1065 |
| FlameF0X/ChessSLM-PM | 1055 |
| DedeProGames/Chesser-248K-Mini |
Like many language-model-based chess systems, ChessSLM has several limitations:
These limitations are common for pure language-model chess agents that do not use external rule engines.
ChessSLM shows that very small language models can achieve meaningful chess performance when trained on domain-specific data.
It serves as a lightweight baseline for exploring LLM-based chess agents and specialized small language models (SLMs).
| 1050 |
| bharathrajcl/chess_llama_68m | 1048 |
| FlameF0X/ChessSLM-RL | 1047 |
| distilbert/distilgpt2 | 1047 |
| Mattimax/EliaChess-70m | 1047 |
| HuggingFaceTB/SmolLM2-135M | 1042 |
| nlpguy/amdchess-v5 | 1041 |
| facebook/opt-125m | 1041 |
| EleutherAI/pythia-14m | 1037 |
| DedeProGames/chennus | 1034 |
| Smilyai-labs/Smily-ultra-1 | 1034 |
| huyvux3005/chessllm_FPT | 1034 |