commit 3ddb0fa7ffb357a9b67c22038634a3b681eae15b Author: ModelHub XC Date: Thu May 21 17:44:12 2026 +0800 初始化项目，由ModelHub XC社区提供模型 Model: AI-ModelScope/R-4B Source: Original Platform diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..d379eb3 --- /dev/null +++ b/.gitattributes @@ -0,0 +1,52 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bin.* filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zstandard filter=lfs diff=lfs merge=lfs -text +*.tfevents* filter=lfs diff=lfs merge=lfs -text +*.db* filter=lfs diff=lfs merge=lfs -text +*.ark* filter=lfs diff=lfs merge=lfs -text +**/*ckpt*data* filter=lfs diff=lfs merge=lfs -text +**/*ckpt*.meta filter=lfs diff=lfs merge=lfs -text +**/*ckpt*.index filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.gguf* filter=lfs diff=lfs merge=lfs -text +*.ggml filter=lfs diff=lfs merge=lfs -text +*.llamafile* filter=lfs diff=lfs merge=lfs -text +*.pt2 filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text + +asset/R-4B.png filter=lfs diff=lfs merge=lfs -text +merges.txt filter=lfs diff=lfs merge=lfs -text +tokenizer.json filter=lfs diff=lfs merge=lfs -text +vocab.json filter=lfs diff=lfs merge=lfs -text \ No newline at end of file diff --git a/README.md b/README.md new file mode 100644 index 0000000..558883a --- /dev/null +++ b/README.md @@ -0,0 +1,230 @@ +--- +base_model: +- Qwen/Qwen3-4B +language: +- en +license: apache-2.0 +pipeline_tag: image-text-to-text +library_name: transformers +--- + +# R-4B: Incentivizing General-Purpose Auto-Thinking Capability in MLLMs via Bi-Mode Annealing and Reinforce Learning + +[[📚 Arxiv Paper](https://arxiv.org/pdf/2508.21113)] [[🤗 Hugging Face](https://huggingface.co/YannQi/R-4B)] [[🤖️ ModelScope](https://huggingface.co/YannQi/R-4B)] [[💻 Code](https://github.com/yannqi/R-4B)] + +
+logo +
+ +
+ R-4B Performance +
+ +## ⭐️ Introduction + +In this repo, we present **R-4B**, a multimodal large language model designed for general-purpose auto-thinking, autonomously switching between step-by-step thinking and direct response generation based on task complexity. This capability enables R-4B to deliver high-quality responses while significantly improving inference efficiency and reducing computational costs. + +The development of R-4B follows a two-stage training paradigm: +(1) Bi-mode Annealing, which establishes both thinking and non-thinking capabilities for VQA; and +(2) Bi-mode Policy Optimization (BPO), which enables the model to adaptively switch between thinking and non-thinking modes based on input demands. + +## 🚀 Key Features + +- 🧠 **Think Smart, Act Fast: Adaptive & Controllable Thinking!** + Our model provides three-mode control over the response process. + + - **Auto-thinking Mode:** Unleash **auto-thinking** that works across general topics, from simple Q&A to complex scientific analysis. It saves time and computation by thinking only when it matters. + - **Support Manual Control:** Explicitly command the model to use its `thinking` or `non-thinking` capabilities, enabling you to make your choices for every job. +- 🏆 **Strong Performance, Open for Everyone!** + Our model is now **fully open-source**. It achieves **state-of-the-art performance** among models of comparable size. + +## 📢 News + +- **[2025.08.20]** 🚀 **vLLM Support is Here!** Our R-4B model is now fully compatible with [vLLM](https://github.com/vllm-project/vllm) for high-performance inference. +- **[2025.08.18]** 🏆 **Top Rank Achieved!** We are thrilled to announce that R-4B is now ranked #1 among all open-source models on the [OpenCompass Multi-modal Reasoning Leaderboard](https://rank.opencompass.org.cn/leaderboard-multimodal-reasoning/?m=REALTIME)! +- **[2025.08.11]** 🥇 **Rank #1!** R-4B ranks first under 20B parameters on the [OpenCompass Multi-modal Academic Leaderboard](https://rank.opencompass.org.cn/leaderboard-multimodal/?m=REALTIME)! +- **[2025.08.05]** 🎉 **R-4B is Released!** Our model is now publicly available. You can download it from [Hugging Face](https://huggingface.co/YannQi/R-4B). + +## 🔥 Quickstart + +Below, we provide simple examples to show how to use R-4B with 🤗 Transformers. + +### Using 🤗 Transformers to Chat + +> [!NOTE] +> Users can dynamically control the model's response by selecting one of three modes (`auto-thinking`, `thinking`, or `non-thinking`) with `thinking_mode`. `thinking_mode=auto` for `auto-thinking` mode; `thinking_mode=long` for `thinking` mode; `thinking_mode=short` for `non-thinking` mode. +> Default is `auto-thinking`. + +```python +import requests +from PIL import Image +import torch +from transformers import AutoModel, AutoProcessor + +model_path = "YannQi/R-4B" + +# Load model +model = AutoModel.from_pretrained( + model_path, + torch_dtype=torch.float32, + trust_remote_code=True, +).to("cuda") + +# Load processor +processor = AutoProcessor.from_pretrained(model_path, trust_remote_code=True) + +# Define conversation messages +messages = [ + { + "role": "user", + "content": [ + { + "type": "image", + "image": "http://images.cocodataset.org/val2017/000000039769.jpg", + }, + {"type": "text", "text": "Describe this image."}, + ], + } +] + +# Apply chat template +text = processor.apply_chat_template( + messages, + tokenize=False, + add_generation_prompt=True, + thinking_mode="auto" +) + +# Load image +image_url = "http://images.cocodataset.org/val2017/000000039769.jpg" +image = Image.open(requests.get(image_url, stream=True).raw) + +# Process inputs +inputs = processor( + images=image, + text=text, + return_tensors="pt" +).to("cuda") + +# Generate output +generated_ids = model.generate(**inputs, max_new_tokens=16384) +output_ids = generated_ids[0][len(inputs.input_ids[0]):] + +# Decode output +output_text = processor.decode( + output_ids, + skip_special_tokens=True, + clean_up_tokenization_spaces=False +) + +# Print result +print("Auto-Thinking Output:", output_text) +``` + + + +### Using vLLM for fast R-4B deployment and inference. + +- We recommend using vLLM for fast R-4B deployment and inference. + +#### Install + +The code of R-4B requires the newest vllm now. Please install from local source: + +```bash +git clone https://github.com/vllm-project/vllm.git +cd vllm +VLLM_USE_PRECOMPILED=1 uv pip install --editable . +``` + +##### Online Serving + +> [!TIP] +> The `thinking_mode` switch is also available in APIs created by [vLLM](https://github.com/vllm-project/vllm). +> Default is `auto-thinking`. + +- Serve + +```bash +vllm serve \ + yannqi/R-4B \ + --served-model-name r4b \ + --tensor-parallel-size 8 \ + --gpu-memory-utilization 0.8 \ + --host 0.0.0.0 \ + --port 8000 \ + --trust-remote-code +``` + +- Openai Chat Completion Client + +```python +import base64 +from PIL import Image +from openai import OpenAI + + +# Set OpenAI's API key and API base to use vLLM's API server. +openai_api_key = "EMPTY" +openai_api_base = "http://localhost:8000/v1" + +client = OpenAI( + api_key=openai_api_key, + base_url=openai_api_base, +) + +# image url +image_messages = [ + { + "role": "user", + "content": [ + { + "type": "image_url", + "image_url": { + "url": "http://images.cocodataset.org/val2017/000000039769.jpg" + }, + }, + {"type": "text", "text": "Describe this image."}, + ], + }, +] + + + +chat_response = client.chat.completions.create( + model="r4b", + messages=image_messages, + max_tokens=16384, + extra_body={ + "chat_template_kwargs": {"thinking_mode": "auto"}, + }, +) +print("Chat response:", chat_response) +``` + +## 📈 Experimental Results + +
+ R-4B Performance +
+ +1. R-4B establishes itself with powerful, state-of-the-art perceptual abilities that are competitive with larger models. +2. In evaluation sets that require complex logical reasoning and mathematical problem-solving, such as WeMath, MathVerse, and LogicVista, R-4B displays a strong performance curve. This highlights its advanced adaptive thinking capacity for logical deduction and solving complex quantitative problems. + +## ✒️ Citation + +``` +@misc{yang2025r4bincentivizinggeneralpurposeautothinking, + title={R-4B: Incentivizing General-Purpose Auto-Thinking Capability in MLLMs via Bi-Mode Annealing and Reinforce Learning}, + author={Qi Yang and Bolin Ni and Shiming Xiang and Han Hu and Houwen Peng and Jie Jiang}, + year={2025}, + eprint={2508.21113}, + archivePrefix={arXiv}, + primaryClass={cs.CV}, + url={https://arxiv.org/abs/2508.21113}, +} +``` + +## Acknowledgements + +R-4B is developed based on the codebases of the following projects: [LLaVA-Next](https://github.com/LLaVA-VL/LLaVA-NeXT), [SigLIP2](https://huggingface.co/google/siglip2-so400m-patch14-384), [Qwen3](https://github.com/QwenLM/Qwen3), [Qwen2.5-VL](https://github.com/QwenLM/Qwen2.5-VL), [VLMEvalKit](https://github.com/open-compass/VLMEvalKit). We sincerely thank these projects for their outstanding work. \ No newline at end of file diff --git a/added_tokens.json b/added_tokens.json new file mode 100644 index 0000000..5a73856 --- /dev/null +++ b/added_tokens.json @@ -0,0 +1,30 @@ +{ + "": 151668, + "": 151658, + "": 151666, + "": 151669, + "": 151667, + "": 151657, + "": 151665, + "