Update README.md

README.md

@@ -28,17 +28,18 @@ AlpaGo is an adapter model trained using the Qlora technique on top of the GPT-N
 You can utilize AlpaGo to perform natural language processing tasks. Here's an example of how to use it:
 
 ```python
-from alphago import AlpaGo
-
-# Load the AlpaGo model
-model = AlpaGo()
-
-# Example input sentence
-input_text = "Hello, AlpaGo!"
-
-# Send the sentence to the model and get the results
-output = model.process_text(input_text)
-
-# Print the output
-print(output)
-```
+from peft import PeftModel
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
+
+model_id = "EleutherAI/gpt-neox-20b"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+bnb_config = BitsAndBytesConfig(
+    load_in_4bit=True,
+    bnb_4bit_use_double_quant=True,
+    bnb_4bit_quant_type="nf4",
+    bnb_4bit_compute_dtype=torch.bfloat16
+)
+model = AutoModelForCausalLM.from_pretrained(model_id, quantization_config=bnb_config, device_map={"":0})
+model = PeftModel.from_pretrained(model, "myzens/AlpaGo")
+```