samfatnassi commited on
Commit
4cee3f3
·
verified ·
1 Parent(s): ddb8459

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +2 -2
README.md CHANGED
@@ -18,7 +18,7 @@ tags:
18
 
19
 
20
 
21
- This dataset is a high-fidelity, pre-processed collection of over **1 Billion stellar records** derived from the **European Space Agency (ESA) Gaia Mission (Data Release 3)**. It is specifically curated for large-scale galactic archaeology, 3D mapping, and training advanced machine learning models like **SADIM-54M**.
22
 
23
  ### 1. Dataset Overview
24
  The dataset provides a comprehensive snapshot of the Milky Way, covering astrometric, kinematic, and photometric parameters. It has been optimized for high-performance computing and AI-driven astronomical frameworks.
@@ -50,7 +50,7 @@ dataset = load_dataset("samfatnassi/gaia-dr3", split="train", streaming=True)
50
  star_record = next(iter(dataset))
51
  print(star_record)
52
 
53
- 4. Integration with SADIM-54M
54
  This dataset serves as the foundational "knowledge base" for the SADIM-54M Model. While the dataset provides the raw observational facts, the model provides the analytical intelligence to predict and classify these stars.
55
  5. Research & Ethics (Open Science)
56
  This dataset is released under the Apache 2.0 License. It is provided as a contribution to Open Science and Humanity, encouraging researchers, students, and developers worldwide to explore the mysteries of our galaxy without boundaries.
 
18
 
19
 
20
 
21
+ This dataset is a high-fidelity, pre-processed collection of over **1 Billion stellar records** derived from the **European Space Agency (ESA) Gaia Mission (Data Release 3)**. It is specifically curated for large-scale galactic archaeology, 3D mapping, and training advanced machine learning models like **SADIM-V2 77M**.
22
 
23
  ### 1. Dataset Overview
24
  The dataset provides a comprehensive snapshot of the Milky Way, covering astrometric, kinematic, and photometric parameters. It has been optimized for high-performance computing and AI-driven astronomical frameworks.
 
50
  star_record = next(iter(dataset))
51
  print(star_record)
52
 
53
+ 4. Integration with SADIM-V2
54
  This dataset serves as the foundational "knowledge base" for the SADIM-54M Model. While the dataset provides the raw observational facts, the model provides the analytical intelligence to predict and classify these stars.
55
  5. Research & Ethics (Open Science)
56
  This dataset is released under the Apache 2.0 License. It is provided as a contribution to Open Science and Humanity, encouraging researchers, students, and developers worldwide to explore the mysteries of our galaxy without boundaries.