Update README.md

README.md

@@ -17,7 +17,62 @@ Give the model a passage and it will generate a question about the passage.
 I used [flax summarization script](https://github.com/huggingface/transformers/tree/master/examples/flax/summarization) and a TPU v3-8. Summarization expects a text column and a summary column. For question generation training, use the context column instead of text column and question instead of summary column.
 
 
-There is no guarantee that it will produce a question in the language of the passage, but it usually does.
+There is no guarantee that it will produce a question in the language of the passage, but it usually does. Lower resource languages will likely have lower quality questions.
+
+
+## Using the model
+
+#### PyTorch version
+```python
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+  
+tokenizer = AutoTokenizer.from_pretrained("nbroad/mt5-base-qgen")
+model = AutoModelForSeq2SeqLM.from_pretrained("nbroad/mt5-base-qgen", from_flax=True)
+
+text = "Hugging Face has seen rapid growth in its \
+popularity since the get-go. It is definitely doing\
+ the right things to attract more and more people to \
+ its platform, some of which are on the following lines:\
+Community driven approach through large open source repositories \
+along with paid services. Helps to build a network of like-minded\
+ people passionate about open source. \
+Attractive price point. The subscription-based features, e.g.: \
+Inference based API, starts at a price of $9/month.\
+"
+
+inputs = tokenizer(text, return_tensors="pt")
+output = model.generate(**inputs, max_length=40)
+
+tokenizer.decode(output[0], skip_special_tokens=True)
+# What is Hugging Face's price point?
+```
+
+#### Flax version
+```python
+from transformers import AutoTokenizer, FlaxAutoModelForSeq2SeqLM
+  
+tokenizer = AutoTokenizer.from_pretrained("nbroad/mt5-base-qgen")
+model = FlaxAutoModelForSeq2SeqLM.from_pretrained("nbroad/mt5-base-qgen")
+
+text = "A un año y tres días de que el balón ruede \
+en el Al Bayt Stadium inaugurando el Mundial 2022, \
+ya se han dibujado los primeros bocetos de la próxima \
+Copa del Mundo.13 selecciones están colocadas en el \
+mapa con la etiqueta de clasificadas y tienen asegurado\
+ pisar los verdes de Qatar en la primera fase final \
+ otoñal. Serbia, Dinamarca, España, Países Bajos, \
+ Suiza, Croacia, Francia, Inglaterra, Bélgica, Alemania,\
+  Brasil, Argentina y Qatar, como anfitriona, entrarán en \
+  el sorteo del 1 de abril de 2022 en Doha en el que 32 \
+  países serán repartidos en sus respectivos grupos. \
+"
+
+inputs = tokenizer(text, return_tensors="pt")
+output = model.generate(**inputs, max_length=40)
+
+tokenizer.decode(output["sequences"][0], skip_special_tokens=True)
+# ¿Cuántos países entrarán en el sorteo del Mundial 2022?
+```
 
 
 Model trained on Cloud TPUs from Google's TPU Research Cloud (TRC)