Update README.md

README.md

@@ -11,4 +11,32 @@ tags:
 - deberta-v3
 - mdeberta
 - question-answering
----
+---
+
+# mdeberta-v3-base for QA
+
+This is the [mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) model, fine-tuned using the [SQuAD2.0](https://huggingface.co/datasets/squad_v2) dataset. It's been trained on question-answer pairs, including unanswerable questions, for the task of Extractive Question Answering.
+
+## Overview
+**Language model:** mdeberta-v3-base
+**Language:** English
+**Downstream-task:** Extractive QA
+**Training data:** SQuAD 2.0
+**Eval data:** SQuAD 2.0
+**Infrastructure**: 1x NVIDIA T4
+
+### In Transformers
+```python
+from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
+model_name = "sjrhuschlee/mdeberta-v3-base-squad2"
+# a) Get predictions
+nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
+qa_input = {
+'question': 'Where do I live?',
+'context': 'My name is Sarah and I live in London'
+}
+res = nlp(qa_input)
+# b) Load model & tokenizer
+model = AutoModelForQuestionAnswering.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+```