Create README.md

README.md

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+---
+license: apache-2.0
+tags:
+- MRC
+- TyDiQA
+- Natural Questions
+- SQuAD
+- xlm-roberta-large
+language:
+- multilingual
+---
+*Task*: MRC
+
+# Model description
+
+An XLM-RoBERTa Large reading comprehension model trained from the combination of TyDi, NQ, and SQuAD v1 datasets, starting from a fine-tuned [Tydi xlm-roberta-large](https://huggingface.co/PrimeQA/tydiqa-primary-task-xlm-roberta-large) model.
+
+## Intended uses & limitations
+
+You can use the raw model for the reading comprehension task. Biases associated with the pre-existing language model, xlm-roberta-large, that we used may be present in our fine-tuned model.
+
+## Usage
+
+You can use this model directly with the [PrimeQA](https://github.com/primeqa/primeqa) pipeline for reading comprehension [squad.ipynb](https://github.com/primeqa/primeqa/blob/main/notebooks/mrc/squad.ipynb).
+
+### BibTeX entry and citation info
+
+```bibtex
+@article{kwiatkowski-etal-2019-natural,
+    title = "Natural Questions: A Benchmark for Question Answering Research",
+    author = "Kwiatkowski, Tom  and
+      Palomaki, Jennimaria  and
+      Redfield, Olivia  and
+      Collins, Michael  and
+      Parikh, Ankur  and
+      Alberti, Chris  and
+      Epstein, Danielle  and
+      Polosukhin, Illia  and
+      Devlin, Jacob  and
+      Lee, Kenton  and
+      Toutanova, Kristina  and
+      Jones, Llion  and
+      Kelcey, Matthew  and
+      Chang, Ming-Wei  and
+      Dai, Andrew M.  and
+      Uszkoreit, Jakob  and
+      Le, Quoc  and
+      Petrov, Slav",
+    journal = "Transactions of the Association for Computational Linguistics",
+    volume = "7",
+    year = "2019",
+    address = "Cambridge, MA",
+    publisher = "MIT Press",
+    url = "https://aclanthology.org/Q19-1026",
+    doi = "10.1162/tacl_a_00276",
+    pages = "452--466",
+}
+```
+
+```bibtex
+@article{2016arXiv160605250R,
+       author = {{Rajpurkar}, Pranav and {Zhang}, Jian and {Lopyrev},
+                 Konstantin and {Liang}, Percy},
+        title = "{SQuAD: 100,000+ Questions for Machine Comprehension of Text}",
+      journal = {arXiv e-prints},
+         year = 2016,
+          eid = {arXiv:1606.05250},
+        pages = {arXiv:1606.05250},
+archivePrefix = {arXiv},
+       eprint = {1606.05250},
+}
+```
+
+```bibtex
+@article{clark-etal-2020-tydi,
+    title = "{T}y{D}i {QA}: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages",
+    author = "Clark, Jonathan H.  and
+      Choi, Eunsol  and
+      Collins, Michael  and
+      Garrette, Dan  and
+      Kwiatkowski, Tom  and
+      Nikolaev, Vitaly  and
+      Palomaki, Jennimaria",
+    journal = "Transactions of the Association for Computational Linguistics",
+    volume = "8",
+    year = "2020",
+    address = "Cambridge, MA",
+    publisher = "MIT Press",
+    url = "https://aclanthology.org/2020.tacl-1.30",
+    doi = "10.1162/tacl_a_00317",
+    pages = "454--470",
+}
+```