Update README.md (#2)

- Update README.md (850f931d79ba7f6a7b42ab44b3114a32cc0d9685)


Co-authored-by: Wei Liu <[email protected]>

README.md

@@ -99,7 +99,7 @@ def load_image(image_file, input_size=448, max_num=6):
     pixel_values = torch.stack(pixel_values)
     return pixel_values
 
-path = "OpenGVLab/InternVL-Chat-V1-5"
+path = "AI4Chem/ChemVLM-26B"
 # If you have an 80G A100 GPU, you can put the entire model on a single GPU.
 model = AutoModel.from_pretrained(
     path,
@@ -175,5 +175,6 @@ This project is released under the MIT license.
 
 ## Acknowledgement
 
-ChemVLM is built on [InternVL](https://github.com/OpenGVLab/InternVL).
+ChemVLM is built on [InternVL](https://github.com/OpenGVLab/InternVL). 
+
 InternVL is built with reference to the code of the following projects: [OpenAI CLIP](https://github.com/openai/CLIP), [Open CLIP](https://github.com/mlfoundations/open_clip), [CLIP Benchmark](https://github.com/LAION-AI/CLIP_benchmark), [EVA](https://github.com/baaivision/EVA/tree/master), [InternImage](https://github.com/OpenGVLab/InternImage), [ViT-Adapter](https://github.com/czczup/ViT-Adapter), [MMSegmentation](https://github.com/open-mmlab/mmsegmentation), [Transformers](https://github.com/huggingface/transformers), [DINOv2](https://github.com/facebookresearch/dinov2), [BLIP-2](https://github.com/salesforce/LAVIS/tree/main/projects/blip2), [Qwen-VL](https://github.com/QwenLM/Qwen-VL/tree/master/eval_mm), and [LLaVA-1.5](https://github.com/haotian-liu/LLaVA). Thanks for their awesome work!