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aspect-acl-scibert-scivocab-uncased
malteos/aspect-acl-scibert-scivocab-uncased
aspect-acl-scibert-scivocab-uncased is a machine learning model from malteos. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
A scibert-scivocab-uncased model fine-tuned on the ACL Anthology corpus as in Aspect-based Document Similarity for Research Papers.
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At a glance
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Feb 7, 2023
- SHA
- 756c53ef
Datasets
Model card
From the Hugging Face model README
Aspect-based Document Similarity for Research Papers
A scibert-scivocab-uncased model fine-tuned on the ACL Anthology corpus as in Aspect-based Document Similarity for Research Papers.
See GitHub for more details: https://github.com/malteos/aspect-document-similarity
Demo
<a href="https://colab.research.google.com/github/malteos/aspect-document-similarity/blob/master/demo.ipynb"><img src="https://camo.githubusercontent.com/52feade06f2fecbf006889a904d221e6a730c194/68747470733a2f2f636f6c61622e72657365617263682e676f6f676c652e636f6d2f6173736574732f636f6c61622d62616467652e737667" alt="Google Colab"></a>
You can try our trained models directly on Google Colab on all papers available on Semantic Scholar (via DOI, ArXiv ID, ACL ID, PubMed ID):
<a href="https://colab.research.google.com/github/malteos/aspect-document-similarity/blob/master/demo.ipynb"><img src="https://raw.githubusercontent.com/malteos/aspect-document-similarity/master/demo.gif" alt="Click here for demo"></a>
- Library
- transformers
- Type
- bert
- License
- mit
- Languages
- sci, en, multilingual
- Created
- Mar 2, 2022
- Updated
- Feb 7, 2023