docs: add note about ZeroGPU

app.py

@@ -696,7 +696,7 @@ with gr.Blocks(
 
     gr.Markdown(
         f"""
-        # 🚀 _De Novo_ Peptide Sequencing with InstaNovo
+        # 🚀 _De Novo_ Peptide Sequencing with InstaNovo and InstaNovo+
         Upload your mass spectrometry data file (.mgf, .mzml, or .mzxml) and get peptide sequence predictions.
         Choose your prediction method and decoding options.
 
@@ -710,12 +710,9 @@ with gr.Blocks(
         * **Transformer Decoding Methods:**
              *   **Greedy Search:** use this for optimal performance, has similar performance as Knapsack Beam Search at 5% FDR.
              *   **Knapsack Beam Search:** use this for the best results and highest peptide recall, but is about 10x slower than Greedy Search.
-         *   `delta_mass_ppm` shows the lowest absolute precursor mass error (ppm) across isotopes 0-1 for the final sequence.
          *   Check logs for progress, especially for large files or slower methods.
 
-         **Links:**
-        * [InstaNovo enables diffusion-powered de novo peptide sequencing in large-scale proteomics experiments](https://www.nature.com/articles/s42256-025-01019-5), Eloff, Kalogeropoulos et al. 2025, Nature Machine Intelligence.
-        * [GitHub Repository for InstaNovo](https://github.com/instadeepai/instanovo)
+         This Hugging Face Space is powered by a [ZeroGPU ](https://huggingface.co/docs/hub/en/spaces-zerogpu), which is free but **limited to 5 minutes per day per user**—so if you test with your own files, please use only small files.
          """,
          elem_classes="feedback"
     )
@@ -796,11 +793,16 @@ with gr.Blocks(
     with gr.Accordion("Application Logs", open=True):
         log_display = Log(log_file, dark=True, height=300)
 
+
+    gr.Markdown(""" **Links:**
+        * [GitHub Repository for InstaNovo](https://github.com/instadeepai/instanovo)
+        * [InstaNovo enables diffusion-powered de novo peptide sequencing in large-scale proteomics experiments](https://www.nature.com/articles/s42256-025-01019-5), Eloff, Kalogeropoulos et al. 2025, Nature Machine Intelligence.
+        
+        If you use InstaNovo in your research, please cite:""")
+    
     gr.Markdown(
         value="""
-If you use InstaNovo in your research, please cite:
-
-```bibtex
+```
 @article{eloff_kalogeropoulos_2025_instanovo,
 	title        = {InstaNovo enables diffusion-powered de novo peptide sequencing in large-scale proteomics experiments},
 	author       = {Kevin Eloff and Konstantinos Kalogeropoulos and Amandla Mabona and Oliver Morell and Rachel Catzel and
@@ -815,9 +817,9 @@ If you use InstaNovo in your research, please cite:
 	doi          = {10.1038/s42256-025-01019-5},
 	url          = {https://www.nature.com/articles/s42256-025-01019-5}
 }
+```
 """,
-        show_copy_button=True,
-        label="If you use InstaNovo in your research, please cite:"
+        show_copy_button=True
     )
 
 # --- Launch the App ---