Update README.md

README.md

@@ -13,7 +13,7 @@ license: apache-2.0
 
 This is the merged weights of [bunny-phi-2-siglip-lora](https://huggingface.co/BAAI/bunny-phi-2-siglip-lora).
 
-Bunny is a family of lightweight but powerful multimodal models. It offers multiple plug-and-play vision encoders, like EVA-CLIP, SigLIP and language backbones, including Phi-1.5, StableLM-2 and Phi-2. To compensate for the decrease in model size, we construct more informative training data by curated selection from a broader data source. Remarkably, our Bunny-v1.0-3B model built upon SigLIP and Phi-2 outperforms the state-of-the-art MLLMs, not only in comparison with models of similar size but also against larger MLLM frameworks (7B), and even achieves performance on par with 13B models.
+Bunny is a family of lightweight but powerful multimodal models. It offers multiple plug-and-play vision encoders, like EVA-CLIP, SigLIP and language backbones, including Phi-1.5, StableLM-2, Qwen1.5 and Phi-2. To compensate for the decrease in model size, we construct more informative training data by curated selection from a broader data source. Remarkably, our Bunny-v1.0-3B model built upon SigLIP and Phi-2 outperforms the state-of-the-art MLLMs, not only in comparison with models of similar size but also against larger MLLM frameworks (7B), and even achieves performance on par with 13B models.
 
 The model is pretrained on LAION-2M and finetuned on Bunny-695K.
 More details about this model can be found in [GitHub](https://github.com/BAAI-DCAI/Bunny).
@@ -22,7 +22,13 @@ More details about this model can be found in [GitHub](https://github.com/BAAI-D
 
 # Quickstart
 
-Here we show a code snippet to show you how to use the model with transformers:
+Here we show a code snippet to show you how to use the model with transformers.
+
+Before running the snippet, you need to install the following dependencies:
+
+```shell
+pip install torch transformers accelerate pillow
+```
 
 ```python
 import torch
@@ -69,12 +75,6 @@ output_ids = model.generate(
 print(tokenizer.decode(output_ids[input_ids.shape[1]:], skip_special_tokens=True).strip())
 ```
 
-Before running the snippet, you need to install the following dependencies:
-
-```shell
-pip install torch transformers accelerate pillow
-```
-
 # License
 This project utilizes certain datasets and checkpoints that are subject to their respective original licenses. Users must comply with all terms and conditions of these original licenses.
 The content of this project itself is licensed under the Apache license 2.0.