Update README.md

README.md

@@ -68,8 +68,8 @@ The model can be used with HuggingFace's `transformers` library:
 import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-model = AutoModelForCausalLM.from_pretrained("https://huggingface.co/OuteAI/Lite-Oute-1-65M").to(device)
-tokenizer = AutoTokenizer.from_pretrained("https://huggingface.co/OuteAI/Lite-Oute-1-65M")
+model = AutoModelForCausalLM.from_pretrained("OuteAI/Lite-Oute-1-65M").to(device)
+tokenizer = AutoTokenizer.from_pretrained("OuteAI/Lite-Oute-1-65M")
 def generate_response(message: str, temperature: float = 0.4, repetition_penalty: float = 1.12) -> str:
     # Convert message to PyTorch tensors
     input_ids = tokenizer.encode(