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README.md

@@ -112,7 +112,7 @@ We welcome MLLM benchmark developers to assess our InternVL1.5 and InternVL2 ser
 
 We provide an example code to run InternVL2-Llama3-76B using `transformers`.
 
-We also welcome you to experience the InternVL2 series models in our [online demo](https://internvl.opengvlab.com/). 
+We also welcome you to experience the InternVL2 series models in our [online demo](https://internvl.opengvlab.com/).
 
 > Please use transformers==4.37.2 to ensure the model works normally.
 
@@ -162,7 +162,7 @@ def split_model(model_name):
     device_map = {}
     world_size = torch.cuda.device_count()
     num_layers = {
-        'InternVL2-1B': 24, 'InternVL2-2B': 24, 'InternVL2-4B': 32, 'InternVL2-8B': 32, 
+        'InternVL2-1B': 24, 'InternVL2-2B': 24, 'InternVL2-4B': 32, 'InternVL2-8B': 32,
         'InternVL2-26B': 48, 'InternVL2-40B': 60, 'InternVL2-Llama3-76B': 80}[model_name]
     # Since the first GPU will be used for ViT, treat it as half a GPU.
     num_layers_per_gpu = math.ceil(num_layers / (world_size - 0.5))
@@ -284,7 +284,7 @@ def split_model(model_name):
     device_map = {}
     world_size = torch.cuda.device_count()
     num_layers = {
-        'InternVL2-1B': 24, 'InternVL2-2B': 24, 'InternVL2-4B': 32, 'InternVL2-8B': 32, 
+        'InternVL2-1B': 24, 'InternVL2-2B': 24, 'InternVL2-4B': 32, 'InternVL2-8B': 32,
         'InternVL2-26B': 48, 'InternVL2-40B': 60, 'InternVL2-Llama3-76B': 80}[model_name]
     # Since the first GPU will be used for ViT, treat it as half a GPU.
     num_layers_per_gpu = math.ceil(num_layers / (world_size - 0.5))