diff --git a/mistral/README.md b/mistral/README.md
index eaf07ea5..1bbb385d 100644
--- a/mistral/README.md
+++ b/mistral/README.md
@@ -12,7 +12,7 @@ Install the dependencies:
 pip install -r requirements.txt
 ```
 
-Next, download the model and tokenizer.
+Next, download the model and tokenizer:
 
 ```
 curl -O https://files.mistral-7b-v0-1.mistral.ai/mistral-7B-v0.1.tar
@@ -22,16 +22,16 @@ tar -xf mistral-7B-v0.1.tar
 Then, convert the weights with:
 
 ```
-python convert.py <path_to_torch_weights> mlx_mistral_weights.npz
+python convert.py
 ```
 
 ### Run
 
-Once you've converted the weights to MLX format, you can interact with the
-Mistral model:
+Once you've converted the weights to MLX format, you can generate text with
+the Mistral model:
 
 ```
-python mistral.py mlx_mistral.npz tokenizer.model "hello"
+python mistral.py --prompt "It is a truth universally acknowledged,"  --temp 0
 ```
 
 Run `python mistral.py --help` for more details.
diff --git a/mistral/mistral.py b/mistral/mistral.py
index 57a35585..e846ebfd 100644
--- a/mistral/mistral.py
+++ b/mistral/mistral.py
@@ -253,6 +253,12 @@ if __name__ == "__main__":
         default=100,
         help="Maximum number of tokens to generate",
     )
+    parser.add_argument(
+        "--temp",
+        help="The sampling temperature.",
+        type=float,
+        default=1.0,
+    )
     parser.add_argument("--seed", type=int, default=0, help="The PRNG seed")
 
     args = parser.parse_args()
@@ -266,7 +272,7 @@ if __name__ == "__main__":
     print(args.prompt, end="", flush=True)
     prompt = mx.array(tokenizer.encode(args.prompt))
     tokens = []
-    for token, _ in zip(generate(prompt, model), range(args.max_tokens)):
+    for token, _ in zip(generate(prompt, model, args.temp), range(args.max_tokens)):
         tokens.append(token)
 
         if (len(tokens) % 10) == 0: