Upload rag_mcp_lora_config.yaml with huggingface_hub

rag_mcp_lora_config.yaml

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+auto_config: true
+
+hf_model_repo: "ASTERIZER/LUNA-100M"
+hf_model_file: "sft_v1/final/model.pth"
+pretrained_ckpt: "Base/out/input_models/luna_sft_v1/model.pth"
+
+train_json: "Base/Datasets/rag_mcp_sft/train.json"
+val_json: "Base/Datasets/rag_mcp_sft/val.json"
+out_dir: "Base/out/sft/rag_mcp_lora"
+tokenizer_dir: "Base/checkpoints/EleutherAI/pythia-160m"
+
+model:
+  vocab_size: 50304
+  seq_len: 1024
+  n_layer: 10
+  n_embd: 768
+  n_head: 12
+
+train:
+  epochs: 2
+  lr_warmup_steps: 100
+  save_interval: 250
+  log_interval: 10
+  eval_interval: 250
+  max_norm: 1.0
+
+optimizer:
+  lr: 2.0e-4
+  min_lr: 2.0e-5
+  weight_decay: 0.0
+  betas: [0.9, 0.95]
+  eps: 1.0e-8
+
+batch:
+  global_batch: 64
+  micro_batch: 8
+  grad_accum: 8
+  auto_probe_batch: true
+  probe_safety: 0.94
+
+dataloader:
+  num_workers: 4
+  pin_memory: true
+
+hardware:
+  precision: "bf16"
+
+lora:
+  rank: 16
+  alpha: 32
+  dropout: 0.05
+  target_modules:
+    - "attn.c_attn"
+    - "attn.c_proj"
+    - "mlp.fc"
+    - "mlp.proj"
+
+eval_prompts:
+  - "Explain what retrieval-augmented generation is and why teams use it."
+  - "Describe the core parts of MCP for an engineer who has never used it."
+  - "Compare RAG and MCP without confusing their roles."
+  - "What are good practices for grounding answers with retrieved context?"
+  - "How can an MCP server expose retrieval capabilities to an AI host?"