Update README.md

README.md

@@ -43,22 +43,24 @@ dtype: bfloat16
 ## 🤗 Usage for HuggingFace
 
 ```python
-!pip install -qU transformers accelerate
+# !pip install -qU transformers accelerate
 
 from transformers import AutoTokenizer, AutoModelForCausalLM
+from transformers import pipeline
 import torch
 
-tokenizer = AutoTokenizer.from_pretrained(model)
-model = AutoModelForCausalLM.from_pretrained("AkimfromParis/Heliotrope-Ely-Swa-slerp-7B")
+model_name = "AkimfromParis/Heliotrope-Ely-Swa-slerp-7B"
 
-pipeline = pipeline("text-generation", model=model, tokenizer=tokenizer, torch_dtype=torch.bfloat16, device_map="auto", trust_remote_code=True)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16)
 
-messages = [{"role": "system", "content": "あなたはAIアシスタントです。"}]
-messages.append({"role": "user", "content": "大谷翔平選手について教えてください"})
+pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, pad_token_id=tokenizer.eos_token_id)
 
-prompt = tokenizer.apply_chat_template(conversation=messages, add_generation_prompt=True, tokenize=False)
-
-pipeline(prompt, max_new_tokens=256, do_sample=False, temperature=0.0, return_full_text=False)
+messages = [
+    {"role": "system", "content": "あなたは誠実で優秀な日本人のアシスタントです。以下のトピックに関する詳細な情報を提供してください。"},
+    {"role": "user", "content": "大谷翔平選手は誰ですか？"},
+    ]
+print(pipe(messages, max_new_tokens=256)[0]['generated_text'][-1])
 ```
 
 # 🔖 Citation