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Open Source Science

https://github.com/amazon-science/structure-aware-language-models

https://github.com/amazon-science/structure-aware-language-models

Science Score: 26.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (3.5%) to scientific vocabulary
Last synced: 6 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: amazon-science
  • License: apache-2.0
  • Language: Python
  • Default Branch: main
  • Size: 21.5 KB
Statistics
  • Stars: 8
  • Watchers: 4
  • Forks: 2
  • Open Issues: 5
  • Releases: 0
Created about 4 years ago · Last pushed over 2 years ago
Metadata Files
Readme Contributing License Code of conduct

README.md

Requirements

numpy==1.19.5 pandas==1.3.3 scikit_learn==1.0.1 torch==1.9.0 torch_geometric==2.0.1 tqdm==4.62.3 transformers==4.11.3

Running procedure

1. construct_graph.py - Constructs the necessary semantic embeddings and graph neighborhood 2. dataloader.py - Builds the text and graph dataloaders. 3. train.py - To train the model on the entire dataset. 4. finetune.py - To finetune the model on marketplace-specific dataset. 5. evaluate.py - To evaluate the model on datasets.

Arguments:

To find model arguments, run: python <script> --help

Code details

construct_graph.py - Constructs the necessary semantic embeddings and graph neighborhood dataloader.py - Builds the text and graph dataloaders. train.py - To train the model on the entire dataset. model.py - Defines the SMLM (Classifier) model. finetune.py - To finetune the model on marketplace-specific dataset. evaluate.py - To evaluate the model on datasets.

Owner

  • Name: Amazon Science
  • Login: amazon-science
  • Kind: organization

GitHub Events

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Last synced: over 1 year ago

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  • Total issues: 3
  • Total pull requests: 3
  • Average time to close issues: N/A
  • Average time to close pull requests: less than a minute
  • Total issue authors: 2
  • Total pull request authors: 1
  • Average comments per issue: 0.67
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 3
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
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Top Authors
Issue Authors
  • CheungZeeCn (2)
  • ChengHSUHSU (1)
Pull Request Authors
  • dependabot[bot] (3)
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dependencies (3)

Dependencies

requirements.txt pypi
  • numpy ==1.19.5
  • pandas ==1.3.3
  • scikit_learn ==1.0.1
  • torch ==1.13.1
  • torch_geometric ==2.0.1
  • tqdm ==4.62.3
  • transformers ==4.11.3