commit e9099c58e0c31b31ffb5d7c8c13afafef2028fe2
Author: ModelHub XC <noreply@modelhub.org.cn>
Date:   Wed Oct 21 00:38:17 2026 +0800

    初始化项目，由ModelHub XC社区提供模型
    
    Model: billygeekourson/philidor-51m
    Source: Original Platform

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diff --git a/README.md b/README.md
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+---
+license: mit
+language:
+  - en
+  - fr
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+  - chess
+  - chess-engine
+  - from-scratch
+  - llama
+  - small-model
+---
+
+# Philidor 51M
+
+*[Version française plus bas](#philidor-51m-français)*
+
+A language model trained **from scratch** to play chess, without ever being
+given a single rule of the game.
+
+It never sees a board. It does not know that pieces, squares or a king exist.
+It receives a sequence of moves in UCI notation and predicts the next one,
+exactly the way a language model predicts the next word.
+
+> *"Pawns are the soul of chess."*
+> François-André Danican Philidor, 1749
+
+## Result
+
+**97.86 % of the moves it proposes are legal**, in free generation, with no
+constraint whatsoever. 95 % confidence interval: [97.65 – 98.05], measured on 20,000
+positions from held-out games.
+
+No rule was ever hard-coded. The model inferred the mechanics of the game from
+790 million moves played by humans.
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+tok = AutoTokenizer.from_pretrained("billygeekourson/philidor-51m")
+model = AutoModelForCausalLM.from_pretrained("billygeekourson/philidor-51m")
+
+ids = tok("e2e4 e7e5 g1f3 b8c6", return_tensors="pt").input_ids
+out = model.generate(ids, max_new_tokens=20, do_sample=True,
+                     temperature=0.6, top_k=20, pad_token_id=0)
+print(tok.decode(out[0], skip_special_tokens=True))
+```
+
+Moves are written in UCI, separated by spaces. **One move is exactly one
+token**, so an 80-ply game takes 80 tokens.
+
+## Playing without ever producing an illegal move
+
+The bundled `vocab_uci.json` lets you mask impossible moves before choosing.
+A single forward pass is enough, and the model keeps its preference ordering
+among the playable moves.
+
+```python
+import json, torch, chess
+from huggingface_hub import hf_hub_download
+
+v = json.load(open(hf_hub_download("billygeekourson/philidor-51m",
+                                   "vocab_uci.json")))
+board = chess.Board()
+board.push_uci("e2e4"); board.push_uci("c7c5")
+
+logits = model(tok("e2e4 c7c5", return_tensors="pt").input_ids).logits[0, -1]
+mask = torch.full_like(logits, float("-inf"))
+for move in board.legal_moves:
+    i = v["stoi"][move.uci()]
+    mask[i] = logits[i]
+
+print(v["itos"][int(mask.argmax())])   # g1f3
+```
+
+## Architecture
+
+Decoder-only Transformer: 16 layers, width 512, 8 attention heads, hidden MLP 1408. Pre-norm, RMSNorm, RoPE, SwiGLU, tied
+embeddings. Context of 256 moves, i.e. a whole game.
+
+**51,397,120 non-embedding parameters** (52,406,272 total).
+
+The architecture happens to match Llama exactly, which was not planned: the
+four building blocks were each chosen on their own merits. The model therefore
+loads as a standard `LlamaForCausalLM`, and the conversion was verified with a
+maximum logit difference of `0.00e+00` at every sequence length.
+
+## Vocabulary
+
+**1,971 tokens**: the 1,968 geometrically possible UCI moves on a chessboard,
+plus `<pad>`, `<bos>` and `<eos>`.
+
+No BPE. The vocabulary is finite and known in advance, which makes legality
+masking possible and spares the model from relearning that `e2` and `e4` form
+a single unit.
+
+## Data
+
+One month of public Lichess archives, July 2026.
+
+| | |
+|---|---|
+| Games read | 89,288,421 |
+| Games kept | 11,035,777 (12.4 %) |
+| Training tokens | 803,780,147 |
+
+Filtering: both players between 1800 and 2600 Elo, bullet excluded, normal
+termination, between 20 and 300 plies. The validation split is done **per
+game**, never per token, so that no game is cut between the two sets.
+
+## Training
+
+A single RTX 3090. **2 hours**, 16,300 steps, one full epoch. bf16, AdamW,
+cosine schedule with warmup, effective batch of 49,152 tokens. Measured MFU:
+64 %.
+
+Final loss: 1.6024 training, 1.6434 validation. Both curves stay
+superimposed, so no overfitting.
+
+## What the model knows
+
+| Metric | Value |
+|---|---|
+| Legal moves in free generation | **97.86 %** |
+| Agreement with the human move, top-1 | 51.42 % |
+| Agreement with the human move, top-5 | 88.72 % |
+| Castling | 100.00 % |
+| En passant | 100.00 % |
+| Promotion | 98.60 % |
+| Getting out of check | 96.60 % |
+
+All measurements are on held-out validation positions, at temperature 1.0 for
+legality and on the argmax for the rest.
+
+## Known limitations
+
+**No board representation.** The model only understands a sequence of moves
+from the initial position. It cannot resume from an arbitrary FEN position.
+
+**About two moves in a hundred are illegal** without masking. For actual play, masking is essential.
+
+**Modest playing strength.** On par with Stockfish capped at skill level 0, it
+drops off at level 1. This is a search-free model: it plays the most probable
+move after a single forward pass, with no lookahead.
+
+**It plays endgames less well than openings.** Positions with few pieces offer
+less statistical regularity to exploit.
+
+## Related model
+
+`philidor-142m`: same method, 142 M parameters, four months of data, twenty hours of training, 98.85 % legal moves. In a 400-game head-to-head it beats this model 305 to 32, a 290 Elo gap.
+
+The interesting part: at equal data volume, tripling the model size barely changes legality, but gains two to three points of agreement with the human move. What drives playing strength is the amount of data, not model size.
+
+## License
+
+MIT for the model. Data comes from the public Lichess archives, released under
+CC0.
+
+---
+---
+
+# Philidor 51M (français)
+
+
+Un modèle de langage entraîné **de zéro** à jouer aux échecs, sans qu'aucune
+règle du jeu ne lui ait jamais été donnée.
+
+Il ne voit pas d'échiquier. Il ne sait pas qu'il existe des pièces, des cases,
+un roi. Il reçoit une suite de coups en notation UCI et prédit le suivant,
+exactement comme un modèle de langage prédit le mot suivant.
+
+> *« Les pions sont l'âme des échecs. »*
+> François-André Danican Philidor, 1749
+
+## Le résultat
+
+**97,86 % des coups qu'il propose sont légaux**, en génération libre, sans
+aucune contrainte. Intervalle de confiance à 95 % : [97,65 – 98,05], mesuré
+sur 20 000 positions issues de parties de validation jamais vues.
+
+Aucune règle n'a été codée. Le modèle a déduit la mécanique du jeu de
+790 millions de coups joués par des humains.
+
+## Utilisation
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+tok = AutoTokenizer.from_pretrained("billygeekourson/philidor-51m")
+model = AutoModelForCausalLM.from_pretrained("billygeekourson/philidor-51m")
+
+ids = tok("e2e4 e7e5 g1f3 b8c6", return_tensors="pt").input_ids
+out = model.generate(ids, max_new_tokens=20, do_sample=True,
+                     temperature=0.6, top_k=20, pad_token_id=0)
+print(tok.decode(out[0], skip_special_tokens=True))
+```
+
+Les coups s'écrivent en UCI, séparés par des espaces. **Un coup vaut exactement
+un token**, donc une partie de 80 demi-coups occupe 80 tokens.
+
+## Jouer sans jamais produire de coup illégal
+
+Le fichier `vocab_uci.json` permet de masquer les coups impossibles avant de
+choisir. Un seul passage avant suffit, et le modèle conserve son ordre de
+préférence entre les coups jouables.
+
+```python
+import json, torch, chess
+
+v = json.load(open("vocab_uci.json"))
+board = chess.Board()
+board.push_uci("e2e4"); board.push_uci("c7c5")
+
+logits = model(tok("e2e4 c7c5", return_tensors="pt").input_ids).logits[0, -1]
+masque = torch.full_like(logits, float("-inf"))
+for coup in board.legal_moves:
+    i = v["stoi"][coup.uci()]
+    masque[i] = logits[i]
+
+print(v["itos"][int(masque.argmax())])   # g1f3
+```
+
+## Architecture
+
+Transformer décodeur : 16 couches, dimension 512, 8 têtes d'attention, MLP
+caché 1408. Pre-norm, RMSNorm, RoPE, SwiGLU, embeddings liés. Contexte de
+256 coups, soit une partie entière.
+
+**51 397 120 paramètres hors embeddings** (52 406 272 au total).
+
+L'architecture correspond exactement à celle de Llama, ce qui n'était pas
+prévu : les quatre briques ont été choisies séparément pour leurs mérites
+propres. Le modèle se charge donc comme un `LlamaForCausalLM` standard, et la
+conversion a été vérifiée : écart maximal de `0.00e+00` sur les logits, à
+toutes les longueurs de séquence.
+
+## Vocabulaire
+
+**1 971 tokens** : les 1 968 coups UCI géométriquement possibles sur un
+échiquier, plus `<pad>`, `<bos>` et `<eos>`.
+
+Pas de BPE. Le vocabulaire est fini et connu d'avance, ce qui rend possible le
+masquage de légalité et évite au modèle de réapprendre que `e2` et `e4`
+forment une seule unité.
+
+## Données
+
+Un mois d'archives publiques Lichess, juillet 2026.
+
+| | |
+|---|---|
+| Parties lues | 89 288 421 |
+| Parties conservées | 11 035 777 (12,4 %) |
+| Tokens d'entraînement | 803 780 147 |
+
+Filtrage : les deux joueurs entre 1800 et 2600 Elo, bullet exclu, terminaison
+normale, entre 20 et 300 demi-coups. Le découpage validation se fait par
+partie et non par token, pour qu'aucune partie ne soit coupée entre les deux
+jeux.
+
+## Entraînement
+
+Une seule RTX 3090. **2 heures**, 16 300 steps, une époque complète. bf16,
+AdamW, cosinus avec chauffe, batch effectif de 49 152 tokens. MFU mesuré : 64 %.
+
+Loss finale : 1,6024 en entraînement, 1,6434 en validation. Les deux courbes
+restent superposées, donc aucun surapprentissage.
+
+## Ce que le modèle sait
+
+| Mesure | Valeur |
+|---|---|
+| Coups légaux en génération libre | **97,86 %** |
+| Accord avec le coup humain, top-1 | 51,42 % |
+| Accord avec le coup humain, top-5 | 88,72 % |
+| Roque | 100,00 % |
+| Prise en passant | 100,00 % |
+| Promotion | 98,60 % |
+| Sortie d'échec | 96,60 % |
+
+Toutes les mesures portent sur des positions de validation jamais vues à
+l'entraînement, à température 1,0 pour la légalité et sur l'argmax pour le
+reste.
+
+## Limites à connaître
+
+**Aucune représentation de l'échiquier.** Le modèle ne comprend qu'une suite de
+coups depuis la position initiale. Il ne sait pas repartir d'une position
+arbitraire donnée en FEN.
+
+**Environ deux coups sur cent sont illégaux** sans masquage. Pour jouer réellement,
+le masquage est indispensable.
+
+**Force de jeu modeste.** À égalité avec Stockfish bridé au niveau 0, il
+décroche au niveau 1. C'est un modèle sans recherche : il joue le coup le plus
+probable après un unique passage avant, sans aucune anticipation.
+
+**Il ne joue pas les finales aussi bien que les ouvertures.** Les positions à
+peu de pièces offrent moins de régularité statistique à exploiter.
+
+## Modèle apparenté
+
+`philidor-142m` : même méthode, 142 M de paramètres, quatre mois de données,
+vingt heures d'entraînement, 98,85 % de coups légaux. En duel direct sur
+400 parties il bat ce modèle-ci 305 à 32, soit un écart de 290 points d'Elo.
+
+Le résultat est instructif : à volume de données égal, tripler la taille du
+modèle ne change presque rien à la légalité, mais gagne deux à trois points
+d'accord avec le coup humain. Ce qui fait la différence de force de jeu, c'est
+le volume de données, pas la taille du modèle.
+
+## Licence
+
+MIT pour le modèle. Les données proviennent des archives publiques Lichess,
+diffusées en CC0.
diff --git a/config.json b/config.json
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--- /dev/null
+++ b/config.json
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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "dtype": "float32",
+  "eos_token_id": 2,
+  "head_dim": 64,
+  "hidden_act": "silu",
+  "hidden_size": 512,
+  "initializer_range": 0.02,
+  "intermediate_size": 1408,
+  "max_position_embeddings": 256,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 8,
+  "num_hidden_layers": 16,
+  "num_key_value_heads": 8,
+  "pad_token_id": 0,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "rope_theta": 10000.0,
+    "rope_type": "default"
+  },
+  "tie_word_embeddings": true,
+  "transformers_version": "5.14.1",
+  "use_cache": true,
+  "vocab_size": 1971
+}
diff --git a/generation_config.json b/generation_config.json
new file mode 100644
index 0000000..92171f3
--- /dev/null
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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "output_attentions": false,
+  "output_hidden_states": false,
+  "pad_token_id": 0,
+  "transformers_version": "5.14.1",
+  "use_cache": true
+}
diff --git a/model.safetensors b/model.safetensors
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+oid sha256:58df45c306b27c1f7b8db008af86afe1cc28f426f4dca609be06436a8c21ca96
+size 209641208
diff --git a/special_tokens_map.json b/special_tokens_map.json
new file mode 100644
index 0000000..c6829dc
--- /dev/null
+++ b/special_tokens_map.json
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+{
+  "bos_token": "<bos>",
+  "eos_token": "<eos>",
+  "pad_token": "<pad>",
+  "unk_token": "<pad>"
+}
\ No newline at end of file
diff --git a/tokenizer.json b/tokenizer.json
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+      "h1b7": 1764,
+      "h1c1": 1765,
+      "h1c6": 1766,
+      "h1d1": 1767,
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+      "h1g3": 1776,
+      "h1h2": 1777,
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+      "h1h6": 1781,
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+      "h2a2": 1784,
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+      "h2b8": 1786,
+      "h2c2": 1787,
+      "h2c7": 1788,
+      "h2d2": 1789,
+      "h2d6": 1790,
+      "h2e2": 1791,
+      "h2e5": 1792,
+      "h2f1": 1793,
+      "h2f2": 1794,
+      "h2f3": 1795,
+      "h2f4": 1796,
+      "h2g1": 1797,
+      "h2g1b": 1798,
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+      "h2g1q": 1800,
+      "h2g1r": 1801,
+      "h2g2": 1802,
+      "h2g3": 1803,
+      "h2g4": 1804,
+      "h2h1": 1805,
+      "h2h1b": 1806,
+      "h2h1n": 1807,
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+      "h2h3": 1810,
+      "h2h4": 1811,
+      "h2h5": 1812,
+      "h2h6": 1813,
+      "h2h7": 1814,
+      "h2h8": 1815,
+      "h3a3": 1816,
+      "h3b3": 1817,
+      "h3c3": 1818,
+      "h3c8": 1819,
+      "h3d3": 1820,
+      "h3d7": 1821,
+      "h3e3": 1822,
+      "h3e6": 1823,
+      "h3f1": 1824,
+      "h3f2": 1825,
+      "h3f3": 1826,
+      "h3f4": 1827,
+      "h3f5": 1828,
+      "h3g1": 1829,
+      "h3g2": 1830,
+      "h3g3": 1831,
+      "h3g4": 1832,
+      "h3g5": 1833,
+      "h3h1": 1834,
+      "h3h2": 1835,
+      "h3h4": 1836,
+      "h3h5": 1837,
+      "h3h6": 1838,
+      "h3h7": 1839,
+      "h3h8": 1840,
+      "h4a4": 1841,
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+      "h4c4": 1843,
+      "h4d4": 1844,
+      "h4d8": 1845,
+      "h4e1": 1846,
+      "h4e4": 1847,
+      "h4e7": 1848,
+      "h4f2": 1849,
+      "h4f3": 1850,
+      "h4f4": 1851,
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+      "h4f6": 1853,
+      "h4g2": 1854,
+      "h4g3": 1855,
+      "h4g4": 1856,
+      "h4g5": 1857,
+      "h4g6": 1858,
+      "h4h1": 1859,
+      "h4h2": 1860,
+      "h4h3": 1861,
+      "h4h5": 1862,
+      "h4h6": 1863,
+      "h4h7": 1864,
+      "h4h8": 1865,
+      "h5a5": 1866,
+      "h5b5": 1867,
+      "h5c5": 1868,
+      "h5d1": 1869,
+      "h5d5": 1870,
+      "h5e2": 1871,
+      "h5e5": 1872,
+      "h5e8": 1873,
+      "h5f3": 1874,
+      "h5f4": 1875,
+      "h5f5": 1876,
+      "h5f6": 1877,
+      "h5f7": 1878,
+      "h5g3": 1879,
+      "h5g4": 1880,
+      "h5g5": 1881,
+      "h5g6": 1882,
+      "h5g7": 1883,
+      "h5h1": 1884,
+      "h5h2": 1885,
+      "h5h3": 1886,
+      "h5h4": 1887,
+      "h5h6": 1888,
+      "h5h7": 1889,
+      "h5h8": 1890,
+      "h6a6": 1891,
+      "h6b6": 1892,
+      "h6c1": 1893,
+      "h6c6": 1894,
+      "h6d2": 1895,
+      "h6d6": 1896,
+      "h6e3": 1897,
+      "h6e6": 1898,
+      "h6f4": 1899,
+      "h6f5": 1900,
+      "h6f6": 1901,
+      "h6f7": 1902,
+      "h6f8": 1903,
+      "h6g4": 1904,
+      "h6g5": 1905,
+      "h6g6": 1906,
+      "h6g7": 1907,
+      "h6g8": 1908,
+      "h6h1": 1909,
+      "h6h2": 1910,
+      "h6h3": 1911,
+      "h6h4": 1912,
+      "h6h5": 1913,
+      "h6h7": 1914,
+      "h6h8": 1915,
+      "h7a7": 1916,
+      "h7b1": 1917,
+      "h7b7": 1918,
+      "h7c2": 1919,
+      "h7c7": 1920,
+      "h7d3": 1921,
+      "h7d7": 1922,
+      "h7e4": 1923,
+      "h7e7": 1924,
+      "h7f5": 1925,
+      "h7f6": 1926,
+      "h7f7": 1927,
+      "h7f8": 1928,
+      "h7g5": 1929,
+      "h7g6": 1930,
+      "h7g7": 1931,
+      "h7g8": 1932,
+      "h7g8b": 1933,
+      "h7g8n": 1934,
+      "h7g8q": 1935,
+      "h7g8r": 1936,
+      "h7h1": 1937,
+      "h7h2": 1938,
+      "h7h3": 1939,
+      "h7h4": 1940,
+      "h7h5": 1941,
+      "h7h6": 1942,
+      "h7h8": 1943,
+      "h7h8b": 1944,
+      "h7h8n": 1945,
+      "h7h8q": 1946,
+      "h7h8r": 1947,
+      "h8a1": 1948,
+      "h8a8": 1949,
+      "h8b2": 1950,
+      "h8b8": 1951,
+      "h8c3": 1952,
+      "h8c8": 1953,
+      "h8d4": 1954,
+      "h8d8": 1955,
+      "h8e5": 1956,
+      "h8e8": 1957,
+      "h8f6": 1958,
+      "h8f7": 1959,
+      "h8f8": 1960,
+      "h8g6": 1961,
+      "h8g7": 1962,
+      "h8g8": 1963,
+      "h8h1": 1964,
+      "h8h2": 1965,
+      "h8h3": 1966,
+      "h8h4": 1967,
+      "h8h5": 1968,
+      "h8h6": 1969,
+      "h8h7": 1970
+    },
+    "unk_token": "<pad>"
+  }
+}
\ No newline at end of file
diff --git a/tokenizer_config.json b/tokenizer_config.json
new file mode 100644
index 0000000..5458d03
--- /dev/null
+++ b/tokenizer_config.json
@@ -0,0 +1,9 @@
+{
+  "tokenizer_class": "PreTrainedTokenizerFast",
+  "model_max_length": 256,
+  "bos_token": "<bos>",
+  "eos_token": "<eos>",
+  "pad_token": "<pad>",
+  "unk_token": "<pad>",
+  "clean_up_tokenization_spaces": false
+}
\ No newline at end of file
diff --git a/vocab_uci.json b/vocab_uci.json
new file mode 100644
index 0000000..a0f9f9d
--- /dev/null
+++ b/vocab_uci.json
@@ -0,0 +1,3954 @@
+{
+  "itos": [
+    "<pad>",
+    "<bos>",
+    "<eos>",
+    "a1a2",
+    "a1a3",
+    "a1a4",
+    "a1a5",
+    "a1a6",
+    "a1a7",
+    "a1a8",
+    "a1b1",
+    "a1b2",
+    "a1b3",
+    "a1c1",
+    "a1c2",
+    "a1c3",
+    "a1d1",
+    "a1d4",
+    "a1e1",
+    "a1e5",
+    "a1f1",
+    "a1f6",
+    "a1g1",
+    "a1g7",
+    "a1h1",
+    "a1h8",
+    "a2a1",
+    "a2a1b",
+    "a2a1n",
+    "a2a1q",
+    "a2a1r",
+    "a2a3",
+    "a2a4",
+    "a2a5",
+    "a2a6",
+    "a2a7",
+    "a2a8",
+    "a2b1",
+    "a2b1b",
+    "a2b1n",
+    "a2b1q",
+    "a2b1r",
+    "a2b2",
+    "a2b3",
+    "a2b4",
+    "a2c1",
+    "a2c2",
+    "a2c3",
+    "a2c4",
+    "a2d2",
+    "a2d5",
+    "a2e2",
+    "a2e6",
+    "a2f2",
+    "a2f7",
+    "a2g2",
+    "a2g8",
+    "a2h2",
+    "a3a1",
+    "a3a2",
+    "a3a4",
+    "a3a5",
+    "a3a6",
+    "a3a7",
+    "a3a8",
+    "a3b1",
+    "a3b2",
+    "a3b3",
+    "a3b4",
+    "a3b5",
+    "a3c1",
+    "a3c2",
+    "a3c3",
+    "a3c4",
+    "a3c5",
+    "a3d3",
+    "a3d6",
+    "a3e3",
+    "a3e7",
+    "a3f3",
+    "a3f8",
+    "a3g3",
+    "a3h3",
+    "a4a1",
+    "a4a2",
+    "a4a3",
+    "a4a5",
+    "a4a6",
+    "a4a7",
+    "a4a8",
+    "a4b2",
+    "a4b3",
+    "a4b4",
+    "a4b5",
+    "a4b6",
+    "a4c2",
+    "a4c3",
+    "a4c4",
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+}
\ No newline at end of file