Update README.md

README.md

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 ---
-base_model: ACE-Step/Ace-Step1.5
 library_name: peft
+base_model: ACE-Step/Ace-Step1.5
+license: mit
+pipeline_tag: text-to-audio
+tags:
+- audio
+- music
+- text2music
 ---
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
+<h1 align="center">ACE-Step 1.5</h1>
+<h1 align="center">Pushing the Boundaries of Open-Source Music Generation</h1>
+<p align="center">
+    <a href="https://ace-step.github.io/ace-step-v1.5.github.io/">Project</a> |
+    <a href="https://huggingface.co/collections/ACE-Step/ace-step-15">Hugging Face</a> |
+    <a href="https://modelscope.cn/models/ACE-Step/ACE-Step-v1-5">ModelScope</a> |
+    <a href="https://huggingface.co/spaces/ACE-Step/Ace-Step-v1.5">Space Demo</a> |
+    <a href="https://discord.gg/PeWDxrkdj7">Discord</a>
+</p>
 
 
+![image](https://cdn-uploads.huggingface.co/production/uploads/62dfaf90c42558bcbd0a4f6f/b84r7t0viIw7rKSr_ja9_.png)
 
 ## Model Details
 
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
-
-
-
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## Uses
-
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
-
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
-
-[More Information Needed]
-
-## Training Details
-
-### Training Data
-
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-
-[More Information Needed]
+🚀 **ACE-Step v1.5** is a highly efficient open-source music foundation model designed to bring commercial-grade music generation to consumer hardware. 
 
-### Training Procedure
+### Key Features
 
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+*   **💰 Commercial-Ready:** Unlike many models trained on ambiguous datasets, ACE-Step v1.5 is designed for creators. You can strictly use the generated music for **commercial purposes**.
+*   **📚 Safe & Robust Training Data:** The model is trained on a massive, legally compliant dataset consisting of:
+    *   **Licensed Data:** Professionally licensed music tracks.
+    *   **Royalty-Free / No-Copyright Data:** A vast collection of public domain and royalty-free music.
+    *   **Synthetic Data:** High-quality audio generated via advanced MIDI-to-Audio conversion.
+*   **⚡ Extreme Speed:** Generates a full song in under 2 seconds on an A100 and under 10 seconds on an RTX 3090.
+*   **🖥️ Consumer Hardware Friendly:** Runs locally with less than 4GB of VRAM.
 
-#### Preprocessing [optional]
+### Technical Capabilities
 
-[More Information Needed]
+🌉 At its core lies a novel hybrid architecture where the Language Model (LM) functions as an omni-capable planner: it transforms simple user queries into comprehensive song blueprints—scaling from short loops to 10-minute compositions—while synthesizing metadata, lyrics, and captions via Chain-of-Thought to guide the Diffusion Transformer (DiT). ⚡ Uniquely, this alignment is achieved through intrinsic reinforcement learning relying solely on the model's internal mechanisms, thereby eliminating the biases inherent in external reward models or human preferences. 🎚️
 
+🔮 Beyond standard synthesis, ACE-Step v1.5 unifies precise stylistic control with versatile editing capabilities—such as cover generation, repainting, and vocal-to-BGM conversion—while maintaining strict adherence to prompts across 50+ languages. This paves the way for powerful tools that seamlessly integrate into the creative workflows of music artists, producers, and content creators. 🎸
 
-#### Training Hyperparameters
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
+- **Developed by:** [ACE-STEP]
+- **Model type:** [Text2Music]
+- **Language(s):** [50+ languages]
+- **License:** [MIT]
 
 ## Evaluation
 
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
-
-[More Information Needed]
-
-#### Summary
-
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
-
-[More Information Needed]
+![image](https://cdn-uploads.huggingface.co/production/uploads/62dfaf90c42558bcbd0a4f6f/n9aKi_NhSmlMOgmGzahZi.png)
 
-#### Software
+## 🏗️ Architecture
 
-[More Information Needed]
 
-## Citation [optional]
+![image](https://cdn-uploads.huggingface.co/production/uploads/62dfaf90c42558bcbd0a4f6f/V_d1rTdqkQyoSM8td7OWl.png)
 
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
 
-**BibTeX:**
+## 🦁 Model Zoo
 
-[More Information Needed]
 
-**APA:**
+![image](https://cdn-uploads.huggingface.co/production/uploads/62dfaf90c42558bcbd0a4f6f/B49V0OTKse_FRefTmTPsQ.png)
 
-[More Information Needed]
+### DiT Models
 
-## Glossary [optional]
+| DiT Model | Pre-Training | SFT | RL | CFG | Step | Refer audio | Text2Music | Cover | Repaint | Extract | Lego | Complete | Quality | Diversity | Fine-Tunability | Hugging Face |
+|-----------|:------------:|:---:|:--:|:---:|:----:|:-----------:|:----------:|:-----:|:-------:|:-------:|:----:|:--------:|:-------:|:---------:|:---------------:|--------------|
+| `acestep-v15-base` | ✅ | ❌ | ❌ | ✅ | 50 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | Medium | High | Easy | [Link](https://huggingface.co/ACE-Step/acestep-v15-base) |
+| `acestep-v15-sft` | ✅ | ✅ | ❌ | ✅ | 50 | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ | High | Medium | Easy | [Link](https://huggingface.co/ACE-Step/acestep-v15-sft) |
+| `acestep-v15-turbo` | ✅ | ✅ | ❌ | ❌ | 8 | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ | Very High | Medium | Medium | [Link](https://huggingface.co/ACE-Step/Ace-Step1.5) |
+| `acestep-v15-turbo-rl` | ✅ | ✅ | ✅ | ❌ | 8 | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ | Very High | Medium | Medium | To be released |
 
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+### LM Models
 
-[More Information Needed]
+| LM Model | Pretrain from | Pre-Training | SFT | RL | CoT metas | Query rewrite | Audio Understanding | Composition Capability | Copy Melody | Hugging Face |
+|----------|---------------|:------------:|:---:|:--:|:---------:|:-------------:|:-------------------:|:----------------------:|:-----------:|--------------|
+| `acestep-5Hz-lm-0.6B` | Qwen3-0.6B | ✅ | ✅ | ✅ | ✅ | ✅ | Medium | Medium | Weak | ✅ |
+| `acestep-5Hz-lm-1.7B` | Qwen3-1.7B | ✅ | ✅ | ✅ | ✅ | ✅ | Medium | Medium | Medium | ✅ |
+| `acestep-5Hz-lm-4B` | Qwen3-4B | ✅ | ✅ | ✅ | ✅ | ✅ | Strong | Strong | Strong | ✅ |
 
-## More Information [optional]
 
-[More Information Needed]
+## 🙏 Acknowledgements
 
-## Model Card Authors [optional]
+This project is co-led by ACE Studio and StepFun.
 
-[More Information Needed]
 
-## Model Card Contact
+## 📖 Citation
 
-[More Information Needed]
-### Framework versions
+If you find this project useful for your research, please consider citing:
 
-- PEFT 0.15.2
+```BibTeX
+@misc{gong2026acestep,
+	title={ACE-Step 1.5: Pushing the Boundaries of Open-Source Music Generation},
+	author={Junmin Gong, Yulin Song, Wenxiao Zhao, Sen Wang, Shengyuan Xu, Jing Guo}, 
+	howpublished={\url{https://github.com/ace-step/ACE-Step-1.5}},
+	year={2026},
+	note={GitHub repository}
+}