use candle_core::{DType, Device, Result};
use candle_nn::VarBuilder;
fn main() -> Result<()> {
let path = "models/TinyLlama-Adaptive-Converted/model.safetensors";
let device = Device::Cpu;
unsafe {
let vb = VarBuilder::from_mmaped_safetensors(&[path], DType::F32, &device)?;
println!("Loaded VB.");
let tensor_name = "model.layers.0.mlp.gate_proj.weight_packed";
let shape = (5632, 512, 3);
match vb.get(shape, tensor_name) {
Ok(t) => println!("✅ Loaded successfully: {:?}", t),
Err(e) => println!("❌ Failed to load [5632, 512, 3]: {:?}", e),
}
let shape1 = (5632, 512, 1);
match vb.get(shape1, tensor_name) {
Ok(t) => println!("❓ Loaded [5632, 512, 1]: {:?}", t),
Err(e) => println!("❌ Failed to load [5632, 512, 1]: {:?}", e),
}
match vb.get((8650752,), tensor_name) {
Ok(t) => println!("✅ Loaded flat 3-base: {:?}", t),
Err(e) => println!("❌ Failed to load flat 3-base: {:?}", e),
}
match vb.get((2883584,), tensor_name) {
Ok(t) => println!("❓ Loaded flat 1-base: {:?}", t),
Err(e) => println!("❌ Failed to load flat 1-base: {:?}", e),
}
}
Ok(())
}