Update README.md

README.md

@@ -16,6 +16,18 @@ from PIL import Image
 import librosa
 import requests
 
+model = MM_LLMs.from_pretrained(
+    'mesolitica/malaysian-tinyllama-1.1b-mmmmodal',
+    flash_attention = True,
+    dtype = torch.bfloat16,
+    torch_dtype = torch.bfloat16
+)
+_ = model.cuda()
+
+image_processor = AutoProcessor.from_pretrained('google/siglip-base-patch16-384')
+audio_processor = AutoProcessor.from_pretrained('mesolitica/malaysian-whisper-small')
+tokenizer = AutoTokenizer.from_pretrained('mesolitica/malaysian-tinyllama-1.1b-mmmmodal')
+
 def prepare_dataset(messages, images: List[str] = None, audio: List[str] = None, sr = 16000):
     
     if images is not None:
@@ -73,18 +85,6 @@ def prepare_dataset(messages, images: List[str] = None, audio: List[str] = None,
         
     return outputs
 
-model = MM_LLMs.from_pretrained(
-    'mesolitica/malaysian-tinyllama-1.1b-mmmmodal',
-    flash_attention = True,
-    dtype = torch.bfloat16,
-    torch_dtype = torch.bfloat16
-)
-_ = model.cuda()
-
-image_processor = AutoProcessor.from_pretrained('google/siglip-base-patch16-384')
-audio_processor = AutoProcessor.from_pretrained('mesolitica/malaysian-whisper-small')
-tokenizer = AutoTokenizer.from_pretrained('mesolitica/malaysian-tinyllama-1.1b-mmmmodal')
-
 with open('Persian-cat-breed.jpg', 'wb') as fopen:
     fopen.write(requests.get('https://cdn.beautifulnara.net/wp-content/uploads/2017/12/10201620/Persian-cat-breed.jpg').content)