Add SmolVLM model (#65)

* Add SmolVLM model

examples/smolvlm/README.md

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+## Quick Start
+
+```shell
+cargo run -r --example smolvlm -- --scale 500m --source "images/green-car.jpg" --prompt "What's in it?"
+cargo run -r --example smolvlm -- --scale 500m --source "images/green-car.jpg" --prompt "What color is the car?"
+cargo run -r --example smolvlm -- --scale 500m --source "images/slanted-text-number.jpg" --prompt "What are these numbers?"
+cargo run -r --example smolvlm -- --scale 256m --source "images/Statue-of-Liberty-Island-New-York-Bay.jpg" --prompt "Can you describe this image?"
+```

examples/smolvlm/main.rs

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+use anyhow::Result;
+use usls::{models::SmolVLM, DataLoader, Options, Scale};
+
+#[derive(argh::FromArgs)]
+/// Example
+struct Args {
+    /// device
+    #[argh(option, default = "String::from(\"cpu:0\")")]
+    device: String,
+
+    /// source image
+    #[argh(option, default = "vec![String::from(\"./assets/bus.jpg\")]")]
+    source: Vec<String>,
+
+    /// promt
+    #[argh(option, default = "String::from(\"Can you describe this image?\")")]
+    prompt: String,
+
+    /// scale
+    #[argh(option, default = "String::from(\"256m\")")]
+    scale: String,
+}
+
+fn main() -> Result<()> {
+    tracing_subscriber::fmt()
+        .with_env_filter(tracing_subscriber::EnvFilter::from_default_env())
+        .with_timer(tracing_subscriber::fmt::time::ChronoLocal::rfc_3339())
+        .init();
+    let args: Args = argh::from_env();
+
+    // build model
+    let (options_vision_encoder, options_text_embed, options_decode) =
+        match args.scale.as_str().try_into()? {
+            Scale::Million(256.) => (
+                Options::smolvlm_vision_256m(),
+                Options::smolvlm_text_embed_256m(),
+                Options::smolvlm_decoder_256m(),
+            ),
+            Scale::Million(500.) => (
+                Options::smolvlm_vision_500m(),
+                Options::smolvlm_text_embed_500m(),
+                Options::smolvlm_decoder_500m(),
+            ),
+            _ => unimplemented!(),
+        };
+
+    let mut model = SmolVLM::new(
+        options_vision_encoder
+            .with_model_device(args.device.as_str().try_into()?)
+            .commit()?,
+        options_text_embed
+            .with_model_device(args.device.as_str().try_into()?)
+            .commit()?,
+        options_decode
+            .with_model_device(args.device.as_str().try_into()?)
+            .commit()?,
+    )?;
+
+    // load images
+    let xs = DataLoader::try_read_batch(&args.source)?;
+
+    // run
+    let ys = model.forward(&xs, &args.prompt)?;
+
+    for y in ys.iter() {
+        if let Some(texts) = y.texts() {
+            for text in texts {
+                println!("[User]: {}\n\n[Assistant]:{}", args.prompt, text);
+            }
+        }
+    }
+
+    Ok(())
+}