Update README.md

README.md

@@ -1,5 +1,4 @@
 ---
-# This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
 license: llama3
 language:
 - en
@@ -10,48 +9,58 @@ tags:
 - large language model
 - domain adaptation
 - scientific domain adaptation
-- crystal generation
 - materials copilot
 - information extraction
 - table understanding
 - table data parsing
 ---
+# Model Card for LLaMat-3-Chat
 
-# Model Card for llamat-3-chat
+**LLaMat-3-Chat** is a specialized large language model designed to serve as a copilot for materials research. Finetuned from **LLaMat-3**, this model is adapted for tasks such as information extraction from material science text and tabular data, table parsing, crystal generation, and more.
+
+---
+
+## Overview
+
+- **Model Type:** Large Language Model (LLM)  
+- **Base Model:** LLaMat-3 (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  
+
+---
 
-<!-- Provide a quick summary of what the model is/does. -->
-LLaMat-3-chat is a materials research copilot.
-  
 ## Model Details
- foundational model that is finetuned from LLaMat-3, which is made by continued pretraining of LLaMA-3 on material science tokens. It has instruction following abilities and can be used as a copilot for information extraction from material science textual or tabular data.
-### Model Description
 
-<!-- Provide a longer summary of what this model is. -->
+### Key Features
+- **Instruction Following Abilities:** Optimized for understanding and processing instructions in the material science domain.  
+- **Domain-Specific Expertise:** Pretrained on material science tokens, enabling high performance in scientific applications.  
+- **Applications:** information extraction, table understanding, and parsing data for research tasks.  
 
-- **Developed by:** M3RG, IIT Delhi
-- **Model type:** Large Language Model based on LLaMA-3 architecture
-- **Language(s) (NLP):** English
-- **License:** LLaMA-3
-- **Finetuned from model [optional]:** m3rg-iitd/llamat-3
+### Development and Support
+- **Developed by:** M3RG, 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.  
 
-### Model Sources [optional]
+---
 
-<!-- Provide the basic links for the model. -->
+## Technical Specifications
 
-- **Repository:** https://github.com/M3RG-IITD/llamat
-<!-- - **Paper [optional]:** [More Information Needed] -->
-<!-- - **Demo [optional]:** [More Information Needed] -->
+### Hardware Infrastructure
+- **Pretraining:** 2 Cerebras CS-2 Wafer-Scale Engines (WSE-2)  
+- **Finetuning:** 8 NVIDIA A100 80GB GPUs  
+- **Inferencing:** 1 NVIDIA A100 80GB GPU  
 
+### Software Stack
+- **Frameworks:** PyTorch, Hugging Face Transformers  
 
-### Compute Infrastructure
-This work was supported by the Edinburgh International Data Facility (EIDF) and the Data-Driven Innovation Programme at the University of Edinburgh. The EIDF provided access to Cerebras CS2 clusters for pretraining the language models.
-Link - https://edinburgh-international-data-facility.ed.ac.uk/services/computing/cerebras-cs
+---
 
-This work is also supported by High Performance Computing cluster and Yardi School of AI at IIT Delhi. 
+## Model Sources
+- **Repository:** [LLaMat-3 on GitHub](https://github.com/M3RG-IITD/llamat)  
+- **Compute Resources:** [EIDF Cerebras CS Clusters](https://edinburgh-international-data-facility.ed.ac.uk/services/computing/cerebras-cs)
+
+---
 
-#### Hardware
-Pretraining: 2 CS-2 Cerebras Wafer-Scale Engine (WSE-2)
-Finetuning:  8 NVIDIA-A100 80GB GPUs 
-Inferencing: 1 NVIDIA-A100 80GB GPU
-#### Software
-PyTorch, HuggingFace, Transformers
+This template provides a robust foundation for understanding the **LLaMat-3-Chat** model, its capabilities, and its applications in advancing material science research.