Update README.md

README.md

@@ -16,9 +16,9 @@ model-index:
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-# Llama-2-7b-hf-lora-tokentrans-it
+# ChocoLlama/ChocoLlama-2-7B-tokentrans-instruct
 
-This model is a fine-tuned version of [llama-2-nl/Llama-2-7b-hf-lora-tokentrans-sft](https://huggingface.co/llama-2-nl/Llama-2-7b-hf-lora-tokentrans-sft) on the BramVanroy/ultra_feedback_dutch dataset.
+This model is a fine-tuned version of [ChocoLlama/ChocoLlama-2-7B-tokentrans-base](https://huggingface.co/ChocoLlama/ChocoLlama-2-7B-tokentrans-base) on the BramVanroy/ultra_feedback_dutch dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.3913
 - Rewards/chosen: 0.1776
@@ -30,6 +30,43 @@ It achieves the following results on the evaluation set:
 - Logits/rejected: 1.1696
 - Logits/chosen: 1.5756
 
+# Use the model
+
+```
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained('ChocoLlama/ChocoLlama-2-7B-tokentrans-instruct')
+model = AutoModelForCausalLM.from_pretrained('ChocoLlama/ChocoLlama-2-7B-tokentrans-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 = tokenizer.apply_chat_template(
+    messages,
+    add_generation_prompt=True,
+    return_tensors="pt"
+).to(model.device)
+
+new_terminators = [
+    tokenizer.eos_token_id,
+    tokenizer.convert_tokens_to_ids("<|eot_id|>")
+]
+
+outputs = 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(tokenizer.decode(response, skip_special_tokens=True))
+
+```
+
 ## Model description
 
 More information needed