| --- |
| base_model: |
| - adammoss/Llama-3.1-8B-Cosmology |
| tags: |
| - cosmology |
| - astrophysics |
| - space-science |
| - transformers |
| datasets: |
| - JaySc/CosmoDataDump |
| - MathLLMs/MathVision |
| - MultimodalUniverse/gz10 |
| - MultimodalUniverse/gaia |
| - MultimodalUniverse/legacysurvey |
| - MultimodalUniverse/desi |
| - MultimodalUniverse/sdss |
| - MultimodalUniverse/hsc |
| - MultimodalUniverse/plasticc |
| - MultimodalUniverse/jwst |
| - MultimodalUniverse/btsbot |
| - MultimodalUniverse/tess |
| - ASTROANTS/CosmoPaperQA |
| - msiudek/astroPT_euclid_dataset |
| - openbmb/UltraData-Math |
| - HuggingFaceTB/finemath |
| - SynthLabsAI/Big-Math-RL-Verified |
| - IUTVanguard/PhysicsEval |
| - AethronPhantom/QST |
| - AethronPhantom/Astro |
| - MathGenie/MathCode-Pile-Full |
| language: |
| - en |
| --- |
| |
| # Cosmic-Combo1 |
|
|
| > ⚠️ **Status: Under Active Development & Experimental Lab Environment** |
| > This repository hosts the architectural metadata, dataset mappings, and conceptual framework for an upcoming fine-tuned cosmological model. Active local training configurations are currently being established. |
|
|
| ## Model Description |
|
|
| Cosmic-Combo1 is an experimental fine-tune of [adammoss/Llama-3.1-8B-Cosmology], specifically targeted toward advanced logical reasoning in celestial mechanics, astrophysical data interpretation, and cosmic structure simulation. By grounding the robust cross-modal architecture of Gemma 4 with specialized cosmic datasets, this model aims to serve as an open assistant for analyzing complex cosmological questions. |
|
|
| - **Developed by:** JaySC |
| - **Model type:** Decoder-only Transformer (Llama) |
| - **Language(s) (NLP):** English |
| - **License:** [Apache 2.0](https://huggingface.co/adammoss/Llama-3.1-8B-Cosmology) |
| - **Base Model:** [https://huggingface.co/adammoss/Llama-3.1-8B-Cosmology] from [https://huggingface.co/meta-llama/Llama-3.1-8B] |
|
|
| ### Concept Blueprint |
|
|
| The primary objective of this project is to explore how specialized datasets shape advanced structural logic when injected into top-tier open architectures. |
|
|
| A twin iteration using `Qwen` as a separate, parallel baseline is planned for future development to allow for a direct comparative evaluation between the two architectural frameworks. |
|
|
| --- |
|
|
| ## Training Data & Methodology |
|
|
| This model links directly to specialized cosmological research repositories compiled for targeted knowledge ingestion: |
|
|
| 1. **Synthetic-VQA-Cosmology-Astrophysics-Planc:** Tailored visual-question-answering structures focusing on astrophysics and Planck-scale phenomena. |
|
|
| ### Hyperparameters & Infrastructure (Planned) |
| * **Framework:** PyTorch / Hugging Face Transformers / PEFT (LoRA) |
| * **Target Environment:** Python compilation layer utilizing lightweight compute frameworks, or scalable multi-GPU notebooks for heavy weight generation. |
|
|
| --- |
|
|
| ## Intentions & Ethical Use |
|
|
| ### Intended Use |
| This model is built exclusively for research, education, and experimental data interpretation in the field of space sciences and theoretical physics. |
|
|
| ### Limitations |
| As an un-converged checkpoint, outputs may contain algorithmic hallucinations or physical inaccuracies regarding complex orbital mechanics or mathematical equations. All analytical outputs should be cross-verified against established academic literature. |
|
|
| --- |
|
|
| ## Attribution & Citations |
|
|
| This work is entirely dependent upon, and deeply grateful to, the open weights and research contributions provided by the global AI and astronomy communities: |
|
|
| - **Base Architecture:** Developed by Meta ([https://huggingface.co/meta-llama/Llama-3.1-8B]. |
| - **Data Collections:** Curated and synthetically engineered by open community science repositories hosted on Hugging Face. |
