Update README.md

README.md

@@ -61,6 +61,32 @@ We used LightEval for evaluation, with custom tasks for the French benchmarks. T
 | arc-chall-en      | 36.09            | 42.32                 | 41.04                 | <u>42.24</u>         |
 | hellaswag-en      | 46.96            | <u>66.94</u>          | 64.48                 | 58.55                |
 
+## Code Example
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("kurakurai/Luth-1.7B-Instruct")
+model = AutoModelForCausalLM.from_pretrained("kurakurai/Luth-1.7B-Instruct")
+messages = [
+    {"role": "user", "content": "Quelle est la capitale de la France?"},
+]
+inputs = tokenizer.apply_chat_template(
+    messages,
+    add_generation_prompt=True,
+    tokenize=True,
+    return_dict=True,
+    return_tensors="pt",
+).to(model.device)
+
+outputs = model.generate(**inputs, max_new_tokens=100)
+print(
+    tokenizer.decode(
+        outputs[0][inputs["input_ids"].shape[-1] :], skip_special_tokens=True
+    )
+)
+```
+
 ## Citation
 
 ```bibtex