update code

app.py

@@ -38,14 +38,14 @@ def how_to_load(language):
 def load_model(values, language):
     model = values["model"]
     if not model:
-        text = f"""No model available for {language.capitalize()}. If you trained a model on this language, let us know in\
+        text = f"""No model is available for {language.capitalize()}. If you trained a model on this language, let us know in\
         in the [Community tab](https://huggingface.co/spaces/loubnabnl/the-stack-bot/discussions) to feature your model!\n\
         You can also train your own model on The Stack using the instructions below 🚀"""
         st.write(text)
         if st.button("Fine-tune your own model", key=4):
             st.write("Code available at [GitHub link] + add preview")
     else:
-        text = f"""{model} is a model that was trained on the {language.capitalize()} subset of The Stack. Here's how to use it:"""
+        text = f"""[{model}](hf.co/{model}) is a model trained on the {language.capitalize()} subset of The Stack. Here's how to use it:"""
         code = f"""
         ```python
         from transformers import AutoModelForCausalLM, AutoTokenizer
@@ -106,7 +106,7 @@ if st.session_state["Models trained on dataset"]:
     load_model(languages[selected_language], selected_language)
 
     if languages[selected_language]["model"] and languages[selected_language]["gradio_demo"]:
-        st.write(f"Here's a demo to try the model, for more flexibilty you can use the [Gradio demo]({languages[selected_language]['gradio_demo']}).")
+        st.write(f"Here's a demo to try it, for more flexibilty you can use the original [Gradio demo]({languages[selected_language]['gradio_demo']}).")
         gen_prompt = st.text_area(
         "Generate code with prompt:",
         value="# Implement a function to print hello world",