diff --git a/README.md b/README.md
index c55093f2..8bc324bd 100644
--- a/README.md
+++ b/README.md
@@ -61,7 +61,7 @@ We also provide a some command line based examples using state of the art models
 
 - [LLaMA and LLaMA-v2](./candle-examples/examples/llama/): general LLM.
 - [Falcon](./candle-examples/examples/falcon/): general LLM.
-- [Phi-v1.5](./candle-examples/examples/phi/): a 1.3b general LLM with performance on par with LLaMA-v2 7b.
+- [Phi-v1 and Phi-v1.5](./candle-examples/examples/phi/): a 1.3b general LLM with performance on par with LLaMA-v2 7b.
 - [StableLM-3B-4E1T](./candle-examples/examples/stable-lm/): a 3b general LLM
   pre-trained on 1T tokens of English and code datasets.
 - [Mistral7b-v0.1](./candle-examples/examples/mistral/): a 7b general LLM with
diff --git a/candle-examples/examples/phi/main.rs b/candle-examples/examples/phi/main.rs
index eff329ff..3922b3d5 100644
--- a/candle-examples/examples/phi/main.rs
+++ b/candle-examples/examples/phi/main.rs
@@ -5,7 +5,7 @@ extern crate intel_mkl_src;
 extern crate accelerate_src;
 
 use anyhow::{Error as E, Result};
-use clap::Parser;
+use clap::{Parser, ValueEnum};
 
 use candle_transformers::models::mixformer::{Config, MixFormerSequentialForCausalLM as MixFormer};
 use candle_transformers::models::quantized_mixformer::MixFormerSequentialForCausalLM as QMixFormer;
@@ -110,6 +110,14 @@ impl TextGeneration {
     }
 }
 
+#[derive(Clone, Copy, Debug, ValueEnum)]
+enum WhichModel {
+    #[value(name = "1")]
+    V1,
+    #[value(name = "1.5")]
+    V1_5,
+}
+
 #[derive(Parser, Debug)]
 #[command(author, version, about, long_about = None)]
 struct Args {
@@ -140,11 +148,14 @@ struct Args {
     #[arg(long, short = 'n', default_value_t = 100)]
     sample_len: usize,
 
-    #[arg(long, default_value = "microsoft/phi-1_5")]
-    model_id: String,
+    #[arg(long)]
+    model_id: Option<String>,
 
-    #[arg(long, default_value = "refs/pr/18")]
-    revision: String,
+    #[arg(long, default_value = "1.5")]
+    model: WhichModel,
+
+    #[arg(long)]
+    revision: Option<String>,
 
     #[arg(long)]
     weight_file: Option<String>,
@@ -189,18 +200,42 @@ fn main() -> Result<()> {
 
     let start = std::time::Instant::now();
     let api = Api::new()?;
-    let repo = api.repo(Repo::with_revision(
-        args.model_id,
-        RepoType::Model,
-        args.revision,
-    ));
+    let model_id = match args.model_id {
+        Some(model_id) => model_id.to_string(),
+        None => {
+            if args.quantized {
+                "lmz/candle-quantized-phi".to_string()
+            } else {
+                match args.model {
+                    WhichModel::V1 => "microsoft/phi-1".to_string(),
+                    WhichModel::V1_5 => "microsoft/phi-1_5".to_string(),
+                }
+            }
+        }
+    };
+    let revision = match args.revision {
+        Some(rev) => rev.to_string(),
+        None => {
+            if args.quantized {
+                "main".to_string()
+            } else {
+                match args.model {
+                    WhichModel::V1 => "refs/pr/2".to_string(),
+                    WhichModel::V1_5 => "refs/pr/18".to_string(),
+                }
+            }
+        }
+    };
+    let repo = api.repo(Repo::with_revision(model_id, RepoType::Model, revision));
     let tokenizer_filename = repo.get("tokenizer.json")?;
     let filename = match args.weight_file {
         Some(weight_file) => std::path::PathBuf::from(weight_file),
         None => {
             if args.quantized {
-                api.model("lmz/candle-quantized-phi".to_string())
-                    .get("model-q4k.gguf")?
+                match args.model {
+                    WhichModel::V1 => repo.get("model-v1-q4k.gguf")?,
+                    WhichModel::V1_5 => repo.get("model-q4k.gguf")?,
+                }
             } else {
                 repo.get("model.safetensors")?
             }