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README.md

@@ -13,32 +13,47 @@ framework: pytorch
 
 # SimBot GPT (Level 1)
 
-This is a **from-scratch GPT-style language model** trained using PyTorch.
+SimBot GPT is a **from-scratch GPT-style language model** implemented in **PyTorch**.
+This project is focused on **learning LLM internals**, not on instruction tuning or production use.
 
-### Training
-- Architecture: Decoder-only Transformer
-- Objective: Causal Language Modeling
-- Dataset: Simdega / domain-specific text
-- Purpose: Learning LLM internals (not instruction-tuned)
+---
+
+## Model Overview
+
+- **Architecture:** Decoder-only Transformer (GPT-like)
+- **Training Objective:** Causal Language Modeling
+- **Dataset:** Domain-specific text (Simdega / regional data)
+- **Purpose:** Educational (understanding how LLMs work internally)
+
+⚠️ This is a **base language model**, not instruction-tuned and not grounded with RAG.
+
+---
 
-### Files
-- `simbot.pt` — model weights
+## Repository Contents
+
+- `simbot.safetensors` — model weights (safe & HF-recommended format)
 - `tokenizer.json` — BPE tokenizer
-- `model/simbot.py` — model architecture
+- `config.json` — model hyperparameters
+- `model/simbot.py` — model architecture (PyTorch)
+
+---
 
-### Usage (example)
+## Usage Example
 
 ```python
-import torch
+import json
+from safetensors.torch import load_file
 from tokenizers import Tokenizer
 from model.simbot import SIMGPT
-import json
 
+# Load tokenizer
 tokenizer = Tokenizer.from_file("tokenizer.json")
 
+# Load config
 with open("config.json") as f:
     cfg = json.load(f)
 
+# Build model
 model = SIMGPT(
     vocab_size=cfg["vocab_size"],
     block_size=cfg["block_size"],
@@ -47,5 +62,7 @@ model = SIMGPT(
     d_model=cfg["d_model"]
 )
 
-model.load_state_dict(torch.load("gpt.pt", map_location="cpu"))
+# Load weights
+state_dict = load_file("simbot.safetensors")
+model.load_state_dict(state_dict)
 model.eval()

simbot.safetensors

@@ -0,0 +1,3 @@
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+oid sha256:025e9428d136cc01078962849d732c1ee63dd73899f995246893ca58e0ab4b97
+size 48078808