cakshat/AlloyBERT
Introducing AlloyBERT: a transformer encoder-based model for predicting alloy properties from textual inputs. Leveraging RoBERTa and self-attention mechanisms, it achieves superior performance, surpassing shallow models.
This tool helps materials scientists and metallurgists quickly predict the mechanical properties of new alloy compositions. By inputting textual descriptions or compositions of an alloy, you can get predictions for properties like elastic modulus and yield strength. This is ideal for researchers in materials science and engineering who are designing new alloys.
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Use this if you need to rapidly estimate the mechanical properties of various alloy compositions without extensive physical testing.
Not ideal if you require highly precise, experimentally verified property values for final product certification or manufacturing specifications.
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12
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Language
Python
License
MIT
Category
Last pushed
Aug 05, 2024
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