Update README.md

README.md

@@ -27,6 +27,19 @@ We release InternLM-XComposer2 series in two versions:
 - InternLM-XComposer2-VL: The pretrained VLLM model with InternLM2 as the initialization of the LLM, achieving strong performance on various multimodal benchmarks.
 - InternLM-XComposer2: The finetuned VLLM for *Free-from Interleaved Text-Image Composition*.
 
+
+### Import from Transformers
+To load the InternLM-XComposer2-VL-7B model using Transformers, use the following code:
+```python
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+ckpt_path = "internlm/internlm-xcomposer2-vl-7b"
+tokenizer = AutoTokenizer.from_pretrained(ckpt_path, trust_remote_code=True).cuda()
+# Set `torch_dtype=torch.float16` to load model in float16, otherwise it will be loaded as float32 and might cause OOM Error.
+model = AutoModelForCausalLM.from_pretrained(ckpt_path, torch_dtype=torch.float16, trust_remote_code=True).cuda()
+model = model.eval()
+```
+
 ## Quickstart
 We provide a simple example to show how to use InternLM-XComposer with 🤗 Transformers.
 ```python
@@ -52,31 +65,5 @@ print(response)
 
 ```
 
-### Import from Transformers
-To load the InternLM-XComposer2-VL-7B model using Transformers, use the following code:
-```python
-import torch
-from PIL import image
-from transformers import AutoTokenizer, AutoModelForCausalLM
-ckpt_path = "internlm/internlm-xcomposer2-vl-7b"
-tokenizer = AutoTokenizer.from_pretrained(ckpt_path, trust_remote_code=True).cuda()
-# Set `torch_dtype=torch.float16` to load model in float16, otherwise it will be loaded as float32 and might cause OOM Error.
-model = AutoModelForCausalLM.from_pretrained(ckpt_path, torch_dtype=torch.float16, trust_remote_code=True).cuda()
-model = model.eval()
-```
-
-### 通过 Transformers 加载
-通过以下的代码加载 InternLM-XComposer2-VL-7B 模型
-
-```python
-import torch
-from transformers import AutoTokenizer, AutoModelForCausalLM
-ckpt_path = "internlm/internlm-xcomposer2-vl-7b"
-tokenizer = AutoTokenizer.from_pretrained(ckpt_path, trust_remote_code=True).cuda()
-# `torch_dtype=torch.float16` 可以令模型以 float16 精度加载，否则 transformers 会将模型加载为 float32，导致显存不足
-model = AutoModelForCausalLM.from_pretrained(ckpt_path, torch_dtype=torch.float16, trust_remote_code=True).cuda()
-model = model.eval()
-```
-
 ### Open Source License
 The code is licensed under Apache-2.0, while model weights are fully open for academic research and also allow free commercial usage. To apply for a commercial license, please fill in the application form (English)/申请表（中文）. For other questions or collaborations, please contact [email protected].