Add model card and metadata

This PR adds a model card and missing metadata, including `pipeline_tag`, `library_name`, and `license`. It also links the model to its corresponding paper on HF中国镜像站 and updates the badge links to standard Markdown format.

Files changed (1) hide show

README.md +19 -188

README.md CHANGED Viewed

@@ -1,199 +1,30 @@
 ---
 library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
-## Model Details
-### Model Description
-<!-- Provide a longer summary of what this model is. -->
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-- **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]
-### Training Procedure
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-#### Preprocessing [optional]
-[More Information Needed]
-#### 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]
-## 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]
-#### Software
-[More Information Needed]
-## Citation [optional]
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-**BibTeX:**
-[More Information Needed]
-**APA:**
-[More Information Needed]
-## Glossary [optional]
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-[More Information Needed]
-## More Information [optional]
-[More Information Needed]
-## Model Card Authors [optional]
-[More Information Needed]
-## Model Card Contact
-[More Information Needed]

 ---
+pipeline_tag: robotics
 library_name: transformers
+license: apache-2.0
+tags: [robotics, agent, computer-vision, llm]
 ---
+# <span style="font-size:30px;">STEVE-R1: Towards Long Reasoning Computer-use Agents</span>
+[![Hugging Face Paper](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Paper-orange)](https://huggingface.co/papers/2503.12532)
+[![HF中国镜像站 Models](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Models-blue)](https://huggingface.co/Fanbin/STEVE-R1-7B-SFT)
+[![HF中国镜像站 Data](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Data-green)](https://huggingface.co/datasets/Fanbin/waa_steve_trajectories)
+We evaluate the performance of the **STEVE-R1 agent** on both in-domain WindowsAgentArena (Windows 11 OS) and out-of-domain OSWorld (Ubuntu OS) benchmarks. The evaluation involves 16 attempts per task, with task completion rates recorded as the primary metric. In the in-domain Windows 11 setting, the STEVE-R1 agent demonstrated a **14%** higher task completion rate compared to the previous open-source state-of-the-art model, UI-TARS-7B-DPO. Furthermore, in the out-of-domain Ubuntu OS environment, where STEVE-R1 was not explicitly trained, it still achieved a **7%** higher task completion rate than UI-TARS-7B-DPO.
+<div align=center>
+<img width="98%" src="assets/performance.png"/>
+</div>
+## Release
+- Currently only the SFT STEVE-R1 model with step-verified training data is released. RL tunning is in progress.
+- 🔥 An improved version **STEVE-R1** is released with long reasoning ability and long image context. We extend the model context length to <b>128K</b> with at most <b>32 screenshot</b> inputs for a single task. The model response length is greatly improved with deepseek-R1 distillation, see the [examples](https://github.com/FanbinLu/STEVE-R1/tree/main/examples). We release the [training data](), [models](https://huggingface.co/Fanbin/STEVE-R1-7B-SFT), and [evaluation trajectories](https://huggingface.co/datasets/Fanbin/waa_steve_trajectories).
+- We release the paper of STEVE: Step Verification Pipeline for Computer-use Agent Training. We propose a single-frame computer-use 7B agent trained with SFT & step-verified KTO.
+## Trajectory Data
+... (rest of the original README content)
+## Citation
+To be added.