Update README.md

README.md

@@ -9,7 +9,7 @@ license: apache-2.0
   <img src="./icon.png" alt="Logo" width="350">
 </p>
 
-📖 [Technical report](https://arxiv.org/abs/2402.11530) | 🏠 [Code](https://github.com/BAAI-DCAI/Bunny) | 🐰 [Demo](https://wisemodel.cn/spaces/baai/Bunny)
+📖 [Technical report](https://arxiv.org/abs/2402.11530) | 🏠 [Code](https://github.com/BAAI-DCAI/Bunny) | 🐰 [Demo](http://bunny.dataoptim.org)
 
 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 Llama-3-8B, Phi-1.5, StableLM-2, Qwen1.5, MiniCPM 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.
 
@@ -76,7 +76,9 @@ output_ids = model.generate(
     input_ids,
     images=image_tensor,
     max_new_tokens=100,
-    use_cache=True)[0]
+    use_cache=True,
+    repetition_penalty=1.0 # increase this to avoid chattering
+)[0]
 
 print(tokenizer.decode(output_ids[input_ids.shape[1]:], skip_special_tokens=True).strip())
 ```