update
Browse files
README.md
CHANGED
@@ -44,13 +44,17 @@ pipeline_tag: text-generation
|
|
44 |
|
45 |
<!-- Provide a longer summary of what this model is. -->
|
46 |
|
47 |
-
Magma is a multimodal agentic AI model that can generate text based on the input text and image. The model is designed for research purposes and aimed at knowledge-sharing and accelerating research in multimodal AI, in particular the multimodal agentic AI. The main innovation of this model lies on the introduction of two technical innovations: Set-of-Mark and Trace-of-Mark
|
48 |
|
49 |
-
|
|
|
|
|
|
|
|
|
50 |
|
51 |
-
The model is
|
52 |
-
|
53 |
-
The model is developed based on Meta LLama-3 as the LLM.
|
54 |
|
55 |
<!-- {{ model_description | default("", true) }}
|
56 |
|
@@ -67,8 +71,8 @@ The model is developed based on Meta LLama-3 as the LLM.
|
|
67 |
<!-- Provide the basic links for the model. -->
|
68 |
|
69 |
- **Paper:** [Project Page](https://microsoft.github.io/Magma/)
|
70 |
-
- **Repository:** [
|
71 |
-
- **Paper:** [arXiv](https://www.arxiv.org/pdf/2502.13130)
|
72 |
|
73 |
<!-- - **Demo [optional]:** {{ demo | default("[More Information Needed]", true)}} -->
|
74 |
|
|
|
44 |
|
45 |
<!-- Provide a longer summary of what this model is. -->
|
46 |
|
47 |
+
Magma is a multimodal agentic AI model that can generate text based on the input text and image. The model is designed for research purposes and aimed at knowledge-sharing and accelerating research in multimodal AI, in particular the multimodal agentic AI. The main innovation of this model lies on the introduction of two technical innovations: **Set-of-Mark** and **Trace-of-Mark**, and the leverage of a **large amount of unlabeled video data** to learn the spatial-temporal grounding and planning. Please refer to our paper for more technical details.
|
48 |
|
49 |
+
## :sparkles: Highlights
|
50 |
+
* **Digital and Physical Worlds:** Magma is the first-ever foundation model for multimodal AI agents, designed to handle complex interactions across both virtual and real environments!
|
51 |
+
* **Versatile Capabilities:** Magma as a single model not only posseesses generic image and videos understanding ability, but alse generate goal-driven visual plans and actions, making it versatile for different agentic tasks!
|
52 |
+
* **State-of-the-art Performance:** Magma achieves state-of-the-art performance on various multimodal tasks, including UI navigation, robotics manipulation, as well as generic image and video understanding, in particular the spatial understanding and reasoning!
|
53 |
+
* **Scalable Pretraining Strategy:** Magma is designed to be **learned scalably from unlabeled videos** in the wild in addition to the existing agentic data, making it strong generalization ability and suitable for real-world applications!
|
54 |
|
55 |
+
NOTE: The model is developed by Microsoft and is funded by Microsoft Research.
|
56 |
+
NOTE: The model is shared by Microsoft Research and is licensed under the MIT License.
|
57 |
+
NOTE: The model is developed based on Meta LLama-3 as the LLM.
|
58 |
|
59 |
<!-- {{ model_description | default("", true) }}
|
60 |
|
|
|
71 |
<!-- Provide the basic links for the model. -->
|
72 |
|
73 |
- **Paper:** [Project Page](https://microsoft.github.io/Magma/)
|
74 |
+
- **Repository:** [Github Repo](https://github.com/microsoft/Magma)
|
75 |
+
- **Paper:** [arXiv Paper](https://www.arxiv.org/pdf/2502.13130)
|
76 |
|
77 |
<!-- - **Demo [optional]:** {{ demo | default("[More Information Needed]", true)}} -->
|
78 |
|