Update README.md

README.md

@@ -61,32 +61,6 @@ We used LightEval for evaluation, with custom tasks for the French benchmarks. T
 | arc-chall-en      | 33.62            | 32.17                 | <u>35.92</u>    |
 | hellaswag-en      | 42.91            | <u>49.56</u>          | 46.96           |
 
-## Code Example
-
-```python
-from transformers import AutoTokenizer, AutoModelForCausalLM
-
-tokenizer = AutoTokenizer.from_pretrained("kurakurai/Luth-0.6B-Instruct")
-model = AutoModelForCausalLM.from_pretrained("kurakurai/Luth-0.6B-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