update

README.md

@@ -21,23 +21,20 @@ Below is a code snippet to use Octopus Planner:
 
 Run below code to use Octopus Planner for a given question:
 ```python
+import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
-model_id = "nexa-collaboration/planning-phi3-128k-full"
-tokenizer_id = "microsoft/Phi-3-mini-128k-instruct"
+model_id = "NexaAIDev/octopus-planning"
 model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto", torch_dtype=torch.bfloat16, trust_remote_code=True)
-tokenizer = AutoTokenizer.from_pretrained(tokenizer_id)
+tokenizer = AutoTokenizer.from_pretrained(model_id)
 
 question = "Find my presentation for tomorrow's meeting, connect to the conference room projector via Bluetooth, increase the screen brightness, take a screenshot of the final summary slide, and email it to all participants"
-
 inputs = f"<|user|>{question}<|end|><|assistant|>"
 input_ids = tokenizer(inputs, return_tensors="pt").to(model.device)
-
 outputs = model.generate(
         input_ids=input_ids["input_ids"], 
         max_length=1024,
         do_sample=False)
-
 res = tokenizer.decode(outputs.tolist()[0])
 print(f"=== inference result ===\n{res}")
 ```