import gradio as gr # Narrative narrative = """ # šŸš€ Welcome to Nexa Marketplace Scientific Machine Learning is powerful — but painful. Researchers struggle with scattered datasets, slow infra, and confusing tooling. **Nexa Marketplace solves this with:** - Pre-curated ML-ready datasets - Simple fine-tuned model consulting - Real tooling for real science """ # Dataset offerings datasets = [ { "name": "🧬 Protein-Lite", "desc": "1K protein samples (ML-ready)", "price": "$5", "link": "https://buy.stripe.com/test_lite" }, { "name": "🧬 Protein-Standard", "desc": "5K protein samples + README", "price": "$20", "link": "https://buy.stripe.com/test_standard" }, { "name": "🧬 Protein-Max", "desc": "10K+ protein samples + entropy rank + docs", "price": "$100", "link": "https://buy.stripe.com/test_max" } ] # Consulting description consulting = """ # šŸ’” LLM + SciML Consulting I fine-tune scientific LLMs on research corpora (300K+ instructions), optimize datasets for training, and build custom inference pipelines. ### šŸ” Example - **Model:** Mistral 7B - **Task:** Hypothesis + methodology generation from papers - **Dataset:** 300K SciML instructions šŸ“© **[Email](mailto:your@email.com)** or **[Book Time](https://calendly.com/your-link)** to get started. """ # Interface with gr.Blocks(title="Nexa Marketplace") as demo: gr.Markdown(narrative) gr.Markdown("## šŸ“¦ Datasets") for ds in datasets: with gr.Row(): gr.Markdown(f"**{ds['name']}** \n{ds['desc']} \nšŸ’° {ds['price']}") gr.Button("Buy", link=ds["link"]) gr.Markdown("## šŸ¤ Consulting") gr.Markdown(consulting) demo.launch()