castorini / wiki-text-100w-fid-large-tqa-reader

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Total runs: 7
24-hour runs: 0
7-day runs: -26
30-day runs: -26
Model's Last Updated: 2023年1月5日

Introduction of wiki-text-100w-fid-large-tqa-reader

Model Details of wiki-text-100w-fid-large-tqa-reader

Fusion-in-Decoder (FiD) is a model described in the following paper:

Izacard, Gautier, and Édouard Grave. Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering . Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume . 2021.

We have replicated FiD training with our Wikipedia corpus variants and incorporated the model into our PyGaggle neural text ranking library.

Our own efforts are described in the paper entitled:

Pre-Processing Matters! Improved Wikipedia Corpora for Open-Domain Question Answering.

This is a FiD-large reader model for the wiki-text-100w corpus variant trained on the TriviaQA dataset.

Runs of castorini wiki-text-100w-fid-large-tqa-reader on huggingface.co

7
Total runs
0
24-hour runs
-30
3-day runs
-26
7-day runs
-26
30-day runs

More Information About wiki-text-100w-fid-large-tqa-reader huggingface.co Model

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https://huggingface.co/castorini/wiki-text-100w-fid-large-tqa-reader

wiki-text-100w-fid-large-tqa-reader install

wiki-text-100w-fid-large-tqa-reader is an open source model from GitHub that offers a free installation service, and any user can find wiki-text-100w-fid-large-tqa-reader on GitHub to install. At the same time, huggingface.co provides the effect of wiki-text-100w-fid-large-tqa-reader install, users can directly use wiki-text-100w-fid-large-tqa-reader installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

wiki-text-100w-fid-large-tqa-reader install url in huggingface.co:

https://huggingface.co/castorini/wiki-text-100w-fid-large-tqa-reader

Url of wiki-text-100w-fid-large-tqa-reader

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castorini
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Total runs: 123
Run Growth: 119
Growth Rate: 96.75%
Updated: 2021年11月5日