Model Card for LLaMat-2

LLaMat-2 is a specialized large language model designed to be a foundational large language model for materials science.

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Overview

• Model Type: Large Language Model (LLM)
• Base Model: LLaMat-2 (continued pretraining of LLaMA-3 on material science data)
• Language: English
• License: LLaMA-3 License
• Tags: Material Science, Domain Adaptation, Table Understanding, Scientific Data Parsing, Materials Copilot

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Model Details

Key Features

• Applications: Can be finetuned for information extraction, table understanding, parsing data for research tasks, and crystal structure generation.

Development and Support

• Developed by: M3RG, IIT Delhi & DAIR, IIT Delhi
• Compute Support:
  • Edinburgh International Data Facility (EIDF): Provided access to Cerebras CS2 clusters for pretraining.
  • IIT Delhi High-Performance Computing Cluster: Supported fine-tuning and inference stages.

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Technical Specifications

Hardware Infrastructure

• Pretraining: 8 NVIDIA A100 80GB GPUs

Software Stack

• Frameworks: PyTorch, Hugging Face Transformers

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Model Sources

• Repository: LLaMat on GitHub
• Compute Resources: EIDF Cerebras CS Clusters

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