update readme

Author: AbdelStark

README.md

@@ -75,7 +75,7 @@ The proof is **transparent** (no trusted setup), **post-quantum** (hash-based, n
 ## Quick Start
 
 ```bash
-git clone https://github.com/abdel/transformer-vm-rs && cd transformer-vm-rs
+git clone https://github.com/AbdelStark/llm-provable-computer && cd llm-provable-computer
 
 # Run a program
 cargo run --bin tvm -- programs/fibonacci.tvm

scripts/validate_onnx.py

@@ -1,5 +1,5 @@
 #!/usr/bin/env python3
-"""Validate exported transformer-vm ONNX programs with ONNX Runtime."""
+"""Validate exported llm-provable-computer ONNX programs with ONNX Runtime."""
 
 from __future__ import annotations
 
@@ -357,7 +357,7 @@ def parse_bool(value: str) -> bool:
 
 def parse_args(argv: list[str]) -> argparse.Namespace:
     parser = argparse.ArgumentParser(
-        description="Validate transformer-vm ONNX exports with onnxruntime."
+        description="Validate llm-provable-computer ONNX exports with onnxruntime."
     )
     parser.add_argument("export_path", help="Export directory or metadata.json path")
     parser.add_argument("--max-steps", type=int, default=4096, help="Maximum execution steps")

src/bin/tvm.rs

@@ -26,7 +26,7 @@ use llm_provable_computer::{BurnExecutionRuntime, BurnTransformerVm};
 type CliBurnBackend = NdArray<f64>;
 
 #[derive(Debug, Parser)]
-#[command(name = "tvm", about = "Run deterministic transformer-vm programs.")]
+#[command(name = "tvm", about = "Run deterministic llm-provable-computer programs.")]
 struct Cli {
     #[command(subcommand)]
     command: Command,

src/config.rs

@@ -105,7 +105,7 @@ impl TransformerVmConfig {
         }
         if self.head_dim() != 2 {
             return Err(VmError::InvalidConfig(format!(
-                "transformer-vm requires head_dim=2, got {}",
+                "llm-provable-computer requires head_dim=2, got {}",
                 self.head_dim()
             )));
         }

src/onnx_export.rs

@@ -440,7 +440,7 @@ fn export_instruction_onnx(
     model.domain = "com.llm_provable_computer".to_string();
     model.model_version = FORMAT_VERSION as i64;
     model.doc_string =
-        "Per-instruction transformer-vm feed-forward export with explicit flag outputs".to_string();
+        "Per-instruction llm-provable-computer feed-forward export with explicit flag outputs".to_string();
     model.graph = MessageField::some(graph);
     model
 }