| --- |
| title: Robe Iniesta Persona Chat |
| emoji: 🎸 |
| colorFrom: red |
| colorTo: gray |
| sdk: gradio |
| sdk_version: 5.12.0 |
| app_file: app.py |
| pinned: false |
| license: apache-2.0 |
| short_description: Spanish persona chat — Qwen 7B + LoRA, under 32B |
| tags: |
| - build-small-hackathon |
| - zerogpu |
| - spanish |
| - persona |
| - lora |
| - qwen2 |
| models: |
| - Qwen/Qwen2.5-7B-Instruct |
| - kabesaml/robe-iniesta-lora |
| --- |
| |
| # Robe Iniesta — Persona Chat |
|
|
| Fine-tuned **Qwen2.5-7B-Instruct** (7B parameters) with a LoRA adapter trained on public interview transcripts. SFT + DPO pipeline. Well under the **32B parameter cap**. |
|
|
| ⚠️ **Fan project.** This is not Robe Iniesta. It may hallucinate biographical facts. |
|
|
| **Live Space:** https://huggingface.co/spaces/build-small-hackathon/robe-iniesta |
|
|
| ## Hackathon submission assets |
|
|
| | Requirement | Status | Link | |
| |---|---|---| |
| | Model ≤32B | ✅ Qwen2.5-7B (7B) | [base model](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) | |
| | Gradio app in Build Small org | ✅ | This Space | |
| | Demo video | ⬜ TODO | **REPLACE:** https://youtu.be/YOUR_DEMO_ID | |
| | Social media post | ⬜ TODO | **REPLACE:** https://x.com/kabesaml/status/YOUR_POST_ID | |
| | ZeroGPU | ✅ | `@spaces.GPU(duration=120)` in `app.py` | |
|
|
| ### Demo video |
|
|
| **Demo video:** https://youtu.be/YOUR_DEMO_ID |
|
|
| 1–3 min walkthrough showing: |
| 1. Opening the Space and waiting for the first GPU response (cold start) |
| 2. Asking "¿Qué significa Extremoduro para ti?" |
| 3. A follow-up question to show multi-turn chat |
| 4. Brief note that it's a style simulation, not the real person |
|
|
| Upload to YouTube (unlisted is fine) or attach video to an X post, then replace the URL above. |
|
|
| ### Social media post |
|
|
| **Social post:** https://x.com/kabesaml/status/YOUR_POST_ID |
|
|
| Example post text: |
|
|
| ``` |
| Built a Spanish persona chatbot for the @huggingface Build Small hackathon 🎸 |
| |
| Qwen2.5-7B (7B) + LoRA, SFT → DPO on public interview transcripts. |
| Runs on ZeroGPU. Under the 32B cap. |
| |
| Try it: https://huggingface.co/spaces/build-small-hackathon/robe-iniesta |
| |
| #BuildSmall #HuggingFace #Qwen #LoRA |
| ``` |
|
|
| Post on X or LinkedIn, then paste the post URL above. |
|
|
| ## Model & training |
|
|
| | Component | Detail | |
| |---|---| |
| | Base model | [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) — **7B params** | |
| | Adapter | [kabesaml/robe-iniesta-lora](https://huggingface.co/kabesaml/robe-iniesta-lora) | |
| | Training | LoRA SFT → DPO preference tuning on Modal A100 | |
| | Quantization | 4-bit NF4 at inference (fits ZeroGPU) | |
| | Source repo | https://github.com/kabesaml/robellm *(update if public)* | |
|
|
| ## Space hardware |
|
|
| Set in Space **Settings → Hardware → ZeroGPU**. |
|
|
| The chat handler uses `@spaces.GPU(duration=120)`. First request after idle may take ~30–60s (model load). |
|
|
| ## Local development |
|
|
| From the robellm repo: |
|
|
| ```bash |
| uv sync --extra dev |
| uv pip install -e ".[train]" spaces |
| uv run python space/app.py |
| ``` |
|
|
