docs: Updated readme

README.md

@@ -1,6 +1,6 @@
 # model2vec-rs
 
-This crate provides a lightweight Rust implementation for loading and running inference on Model2Vec static embedding models (including quantized formats: float32, float16, int8) from either local folders or the Hugging Face Hub.
+This crate provides a lightweight Rust implementation for loading and running inference on [Model2Vec](https://github.com/MinishLab/model2vec) static embedding models from either local folders or the Hugging Face Hub.
 
 ## Quick Start
 
@@ -18,10 +18,11 @@ Make embeddings:
 
 ```rust
 use anyhow::Result;
-use model2vec_rust::inference::StaticModel;
+use model2vec_rs::model::StaticModel;
 
 fn main() -> Result<()> {
     // Load a model from the Hugging Face Hub or a local path
+    // args = (repo_or_path, token, normalize, subfolder)
     let model = StaticModel::from_pretrained("minishlab/potion-base-8M", None, None, None)?;
 
     // Prepare a list of sentences
@@ -48,4 +49,22 @@ cargo run -- encode "Hello world" minishlab/potion-base-8M
 # Multiple lines from a file
 echo -e "Hello world\nRust is awesome" > input.txt
 cargo run -- encode input.txt minishlab/potion-base-8M --output embeds.json
+```
+
+
+Make embeddings with custom encode args:
+
+```rust
+let embeddings = model.encode_with_args(
+    &texts,     // input texts
+    false,      // show progress
+    Some(512),  // max length
+    1204,       // batch size
+    true,       // use multiprocessing
+    10_000,     // multiprocessing threshold
+);
+```
+
+## License
 
+MIT