allenai/specter2
SPECTER 2.0
SPECTER 2.0 is the successor to SPECTER and is capable of generating task specific embeddings for scientific tasks when paired with adapters.
Given the combination of title and abstract of a scientific paper or a short texual query, the model can be used to generate effective embeddings to be used in downstream applications.
Model Details
Model Description
SPECTER 2.0 has been trained on over 6M triplets of scientific paper citations, which are available here.
Post that it is trained on all the SciRepEval training tasks, with task format specific adapters.
Task Formats trained on:
- Classification
- Regression
- Proximity
- Adhoc Search
It builds on the work done in SciRepEval: A Multi-Format Benchmark for Scientific Document Representations and we evaluate the trained model on this benchmark as well.
- Developed by: Amanpreet Singh, Mike D’Arcy, Arman Cohan, Doug Downey, Sergey Feldman
- Shared by : Allen AI
- Model type: bert-base-uncased + adapters
- License: Apache 2.0
- Finetuned from model: allenai/scibert.
Model Sources
- Repository: https://github.com/allenai/SPECTER2_0
- Paper: https://api.semanticscholar.org/CorpusID:254018137
- Demo: Usage
Uses
Direct Use
| Model | Type | Name and HF link |
|---|---|---|
| Base | Transformer | allenai/specter2 |
| Classification | Adapter | allenai/specter2_classification |
| Regression | Adapter | allenai/specter2_regression |
| Retrieval | Adapter | allenai/specter2_proximity |
| Adhoc Query | Adapter | allenai/specter2_adhoc_query |
收录说明：
1、本网页并非 allenai/specter2 官网网址页面，此页面内容编录于互联网，只作展示之用；
2、如果有与 allenai/specter2 相关业务事宜，请访问其网站并获取联系方式；
3、本站与 allenai/specter2 无任何关系，对于 allenai/specter2 网站中的信息，请用户谨慎辨识其真伪。
4、本站收录 allenai/specter2 时，此站内容访问正常，如遇跳转非法网站，有可能此网站被非法入侵或者已更换新网址，导致旧网址被非法使用,
5、如果你是网站站长或者负责人，不想被收录请邮件删除：i-hu#Foxmail.com （#换@）
前往AI网址导航
