Update README.md

README.md

@@ -30,6 +30,43 @@ It achieves the following results on the evaluation set:
 - Logits/rejected: -0.8732
 - Logits/chosen: -0.9594
 
+# use the model
+
+```
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained('ChocoLlama/ChocoLlama-2-7B-instruct')
+model = AutoModelForCausalLM.from_pretrained('ChocoLlama/ChocoLlama-2-7B-instruct', device_map="auto")
+
+messages = [
+    {"role": "system", "content": "Je bent een artificiële intelligentie-assistent en geeft behulpzame, gedetailleerde en beleefde antwoorden op de vragen van de gebruiker."},
+    {"role": "user", "content": "Jacques brel, Willem Elsschot en Jan Jambon zitten op café. Waar zouden ze over babbelen?"},
+]
+
+input_ids = new_tokenizer.apply_chat_template(
+    messages,
+    add_generation_prompt=True,
+    return_tensors="pt"
+).to(new_model.device)
+
+new_terminators = [
+    new_tokenizer.eos_token_id,
+    new_tokenizer.convert_tokens_to_ids("<|eot_id|>")
+]
+
+outputs = new_model.generate(
+    input_ids,
+    max_new_tokens=512,
+    eos_token_id=new_terminators,
+    do_sample=True,
+    temperature=0.8,
+    top_p=0.95,
+)
+response = outputs[0][input_ids.shape[-1]:]
+print(new_tokenizer.decode(response, skip_special_tokens=True))
+
+```
+
 ## Model description
 
 More information needed