Spaces:
Running
Running
Update README.md
#1
by
avisil
- opened
README.md
CHANGED
@@ -7,4 +7,31 @@ sdk: static
|
|
7 |
pinned: false
|
8 |
---
|
9 |
|
10 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
7 |
pinned: false
|
8 |
---
|
9 |
|
10 |
+
<!---
|
11 |
+
Copyright 2022 IBM Corp.
|
12 |
+
|
13 |
+
Licensed under the Apache License, Version 2.0 (the "License");
|
14 |
+
you may not use this file except in compliance with the License.
|
15 |
+
You may obtain a copy of the License at
|
16 |
+
|
17 |
+
http://www.apache.org/licenses/LICENSE-2.0
|
18 |
+
|
19 |
+
Unless required by applicable law or agreed to in writing, software
|
20 |
+
distributed under the License is distributed on an "AS IS" BASIS,
|
21 |
+
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
22 |
+
See the License for the specific language governing permissions and
|
23 |
+
limitations under the License.
|
24 |
+
-->
|
25 |
+
|
26 |
+
<h3 align="center">
|
27 |
+
<img width="350" alt="primeqa" src="docs/_static/img/PrimeQA.png">
|
28 |
+
<p>The prime repository for state-of-the-art Multilingual and Multimedia Question Answering research and development.</p>
|
29 |
+
</h3>
|
30 |
+
|
31 |
+
This is the main location for fine-tuned models from the PrimeQA repository. PrimeQA is a public open source repository that enables researchers and developers to train state-of-the-art models for question answering (QA). By using PrimeQA, a researcher can replicate the experiments outlined in a paper published in the latest NLP conference while also enjoying the capability to download pre-trained models (from an online repository) and run them on their own custom data. PrimeQA is built on top of the [Transformers](https://github.com/huggingface/transformers) toolkit and uses [datasets](https://huggingface.co/datasets/viewer/) and [models](https://huggingface.co/PrimeQA) that are directly downloadable.
|
32 |
+
|
33 |
+
|
34 |
+
The models within PrimeQA supports End-to-end Question Answering. PrimeQA answers questions via
|
35 |
+
- [Information Retrieval](https://github.com/primeqa/primeqa/tree/main/primeqa/ir): Retrieving documents and passages using both traditional (e.g. BM25) and neural (e.g. ColBERT) models
|
36 |
+
- [Multilingual Machine Reading Comprehension](https://huggingface.co/ibm/tydiqa-primary-task-xlm-roberta-large): Extract and/ or generate answers given the source document or passage.
|
37 |
+
- [Multilingual Question Generation](https://huggingface.co/PrimeQA/mt5-base-tydi-question-generator): Supports generation of questions for effective domain adaptation over [tables](https://huggingface.co/PrimeQA/t5-base-table-question-generator) and [multilingual text](https://huggingface.co/PrimeQA/mt5-base-tydi-question-generator).
|