Update README.md

README.md

@@ -21,6 +21,13 @@ processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)
 model = AutoModelForCausalLM.from_pretrained(model_id,trust_remote_code=True)
 # if have a cuda device 
 model.to('cuda')
+# else if you have cpu you can use
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    trust_remote_code=True,
+    device_map='cpu'  # Assure que le modèle est chargé sur le CPU
+    ,torch_dtype=torch.bfloat16  # Charger le modèle en demi-précision
+)
 ```
 
 # LLM Inference
@@ -91,6 +98,8 @@ Create a concise caption that accurately describes the main elements in the imag
 """
 inputs = processor(text=input_text, images=image, return_tensors="pt")
 inputs = {key: value.cuda() for key, value in inputs.items()}
+# NB : if you are using bflot16 ==> 
+inputs = {key: value.to(dtype=model.dtype) if value.dtype == torch.float32 else value for key, value in inputs.items()}
 
 image
 ```