Ultimate Params 998912

README.md

@@ -6,6 +6,7 @@ tags:
 - chess-challenge
 license: mit
 ---
-# Chess Submission
-Submitted by: MDaytek
-Org: LLM-course
+# Chess Submission V3 (ULTIMATE)
+**Submitted by:** MDaytek
+**Organization:** LLM-course
+**Parameters:** 998,912 (Optimized <1M)

config.json

@@ -10,7 +10,7 @@
     "n_layer": 4,
     "n_positions": 256,
     "transformers_version": "4.57.3",
-    "vocab_size": 33,
+    "vocab_size": 1350,
     "auto_map": {
         "AutoConfig": "model.ChessConfig",
         "AutoModelForCausalLM": "model.ChessForCausalLM"

model.py

@@ -4,7 +4,7 @@ from transformers import PreTrainedModel, PretrainedConfig
 from transformers.modeling_outputs import CausalLMOutputWithPast
 class ChessConfig(PretrainedConfig):
     model_type = "chess_lm"
-    def __init__(self, vocab_size=1400, n_positions=256, n_embd=128, n_layer=4, n_head=4, n_ctx=256, tie_word_embeddings=True, **kwargs):
+    def __init__(self, vocab_size=1350, n_positions=256, n_embd=128, n_layer=4, n_head=4, n_ctx=256, tie_word_embeddings=True, **kwargs):
         self.vocab_size, self.n_positions, self.n_embd = vocab_size, n_positions, n_embd
         self.n_layer, self.n_head, self.n_ctx = n_layer, n_head, n_ctx
         self.tie_word_embeddings = tie_word_embeddings

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:fc31bd4ec31ecb27cf5cce087e4d809c3add452e0660fa1d7305f4a9af3cf074
-size 3338147
+oid sha256:2d317f725de1ad7365c08d75cc5567132d45064b2ce15790a9698497e5614450
+size 4012451

vocab.json

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