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README.md

@@ -26,7 +26,7 @@ The architecture is a single-layer associative network trained via Hebbian learn
 |---|---|
 | **Parameters** | 187,200 |
 | **Precision** | 2-bit (Q2_0) |
-| **Model size** | 252 KB |
+| **Model size** | 187 KB weights + 27 KB vocab |
 | **Architecture** | Single-layer associative network |
 | **Context window** | 20 turns |
 | **Output classes** | 1,200 |

config.json

@@ -9,10 +9,7 @@
   "auto_map": {
     "AutoConfig": "configuration_twentyq.TwentyQConfig",
     "AutoModelForCausalLM": "modeling_twentyq.TwentyQForCausalLM",
-    "AutoTokenizer": [
-      "tokenization_twentyq.TwentyQTokenizer",
-      null
-    ]
+    "AutoTokenizer": "tokenization_twentyq.TwentyQTokenizer"
   },
   "torch_dtype": "float32"
 }

tokenizer_config.json

@@ -1,10 +1,7 @@
 {
   "tokenizer_class": "TwentyQTokenizer",
   "auto_map": {
-    "AutoTokenizer": [
-      "tokenization_twentyq.TwentyQTokenizer",
-      null
-    ]
+    "AutoTokenizer": "tokenization_twentyq.TwentyQTokenizer"
   },
   "model_max_length": 4096,
   "pad_token": "<pad>",