Update config.json

config.json

@@ -1,59 +1,59 @@
 {
-  model_name: "Daedalus_1: The Forge of Visionary Innovation",
-  description: "A cutting-edge AI model blending CodeBERT, Codex, T5, SAM, Gemini, and Megatron for transformative innovation.",
-  version: "1.0",
-  author: "Or4cl3 AI Solutions",
-  framework: "PyTorch",
-  python_version: "3.x",
-  deep_learning_framework: "PyTorch",
-  constituent_models: [
+  "model_name": "Daedalus_1: The Forge of Visionary Innovation",
+  "description": "A cutting-edge AI model blending CodeBERT, Codex, T5, SAM, Gemini, and Megatron for transformative innovation.",
+  "version": "1.0",
+  "author": "Or4cl3 AI Solutions",
+  "framework": "PyTorch",
+  "python_version": "3.x",
+  "deep_learning_framework": "PyTorch",
+  "constituent_models": [
     {
-      name: "Or4cl3-1/code-slerp",
-      description: "Empowers Daedalus_1 with expertise in software engineering, code generation, and task-oriented language understanding."
+      "name": "Or4cl3-1/code-slerp",
+      "description": "Empowers Daedalus_1 with expertise in software engineering, code generation, and task-oriented language understanding."
     },
     {
-      name: "Or4cl3-1/SAM-Gemini-BLOOM-OPT-Gopher-Megatron-slerp",
-      description: "Provides Daedalus_1 with a deep, multifaceted understanding of complex concepts, human-like reasoning, and creativity."
+      "name": "Or4cl3-1/SAM-Gemini-BLOOM-OPT-Gopher-Megatron-slerp",
+      "description": "Provides Daedalus_1 with a deep, multifaceted understanding of complex concepts, human-like reasoning, and creativity."
     }
   ],
-  architectural_design: {
-    merge_method: "SLERP (Spherical Linear Interpolation)",
-    selected_layers: 32
+  "architectural_design": {
+    "merge_method": "SLERP (Spherical Linear Interpolation)",
+    "selected_layers": 32
   },
-  capabilities: [
+  "capabilities": [
     "Rapid Prototyping and Code Generation",
     "Multidisciplinary Understanding",
     "Adaptability and Continuous Improvement",
     "Ethical Considerations"
   ],
-  applications: [
+  "applications": [
     "Software Development",
     "Scientific Research",
     "Creative Problem-Solving"
   ],
-  training_data: "Internal and External Datasets",
-  training_steps: 200000,
-  batch_size: 32,
-  learning_rate: 0.0001,
-  max_sequence_length: 1024,
-  num_layers: 24,
-  num_heads: 16,
-  hidden_size: 1024,
-  dropout_rate: 0.2,
-  num_epochs: 20,
-  vocab_size: 50257,
-  max_position_embeddings: 1024,
-  encoder_layers: 24,
-  encoder_ffn_dim: 4096,
-  encoder_attention_heads: 16,
-  decoder_layers: 24,
-  decoder_ffn_dim: 4096,
-  decoder_attention_heads: 16,
-  dropout: 0.2,
-  activation_function: "gelu",
-  initializer_range: 0.02,
-  tie_encoder_decoder: true,
-  tie_word_embeddings: true,
-  output_past: true,
-  pretrained_model_name_or_path: "Or4cl3-1/Daedalus_1-slerp"
+  "training_data": "Internal and External Datasets",
+  "training_steps": 200000,
+  "batch_size": 32,
+  "learning_rate": 0.0001,
+  "max_sequence_length": 1024,
+  "num_layers": 24,
+  "num_heads": 16,
+  "hidden_size": 1024,
+  "dropout_rate": 0.2,
+  "num_epochs": 20,
+  "vocab_size": 50257,
+  "max_position_embeddings": 1024,
+  "encoder_layers": 24,
+  "encoder_ffn_dim": 4096,
+  "encoder_attention_heads": 16,
+  "decoder_layers": 24,
+  "decoder_ffn_dim": 4096,
+  "decoder_attention_heads": 16,
+  "dropout": 0.2,
+  "activation_function": "gelu",
+  "initializer_range": 0.02,
+  "tie_encoder_decoder": true,
+  "tie_word_embeddings": true,
+  "output_past": true,
+  "pretrained_model_name_or_path": "Or4cl3-1/Daedalus_1-slerp"
 }