Update README.md

README.md

@@ -45,6 +45,8 @@ Cost for inference.
 ```python
 from transformers import AutoTokenizer, AutoModelForCausalLM
 
+model_id = "WeeRobots/phi-2-chat-v05"
+
 model = AutoModelForCausalLM.from_pretrained(model_id, device_map={"": 0}, trust_remote_code=True)
 tokenizer = tokenizer = AutoTokenizer.from_pretrained(model_id, use_fast=True, trust_remote_code=True)
 
@@ -63,4 +65,7 @@ with torch.no_grad():
   # but it might continue generating irrelevant text. this way the model will stop at the right place
   model_response = model.generate(**model_input, max_new_tokens=512, eos_token_id=tokenizer.eos_token_id, )
   print(tokenizer.decode(model_result[0], skip_special_tokens=False))
-```
+```
+
+# Non production quality
+Be aware that this model tuning wasn't thoroughly tested, and isn't meant to be used in production, only for experimentation or hobby projects.