docs(qg, nli): add description of modules usage

examples/nli_usage.md

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+# Natural Language Inference module - usage
+
+To use Natural Language Inference(**NLI** module), import it, and use `infer()` function (to get probabilities of different relationships between `premise` and `hypothesis`) or infer_relation()` function (to just get the most probable relationship).
+
+```python
+from knowledge_verificator.nli import infer_relation
+
+if __name__ == '__main__':
+    premise = input("Premise: ")
+    hypothesis = input("Hypothesis: ")
+    print(
+        infer_relation(
+            premise=premise,
+            hypothesis=hypothesis
+        ).value
+    )
+```

examples/qg_usage.md

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+# Question Generation module - usage
+
+To use Question Generation (**QG** module), import it, and use `generate()` method.
+
+```python
+from knowledge_verificator.qg import QuestionGeneration
+
+if __name__ == '__main__':
+    context = input('Provide context: ')
+    answer = input('Answer: ')
+    QG = QuestionGeneration()
+    qa = QG.generate(answer, context)
+    print(qa['question'])
+```