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README.md

@@ -104,3 +104,45 @@ Apache-2.0, consistent with the base model family.
   url    = {https://github.com/SwarmDo/models}
 }
 ```
+
+
+## Use cases
+
+- **Automated bug fixing** in Python repositories — generate a patch, then verify it against the project's tests.
+- **Agentic software engineering** — a coding agent that edits files, runs commands, and self-checks patches.
+- **Image-to-code / visual coding** — turn a chart, plot, or UI screenshot into the code that reproduces it (render-and-compare verified).
+- **Self-hosted / private coding assistant** — runs entirely on your own hardware (vLLM, or GGUF via Ollama / LM Studio); no data leaves your machine.
+- **Best-of-N patch generation** — sample multiple candidate fixes and select the one that passes execution.
+
+## Run it locally (GGUF — Ollama / LM Studio / llama.cpp)
+
+For a one-command local run, use the GGUF build — **no account needed**:
+
+```bash
+ollama run hf.co/SwarmDo/SwarmDo-A1-GGUF:Q4_K_M
+```
+
+GGUF repo: **[SwarmDo/SwarmDo-A1-GGUF](https://huggingface.co/SwarmDo/SwarmDo-A1-GGUF)** (Q4_K_M ~16.5 GB, Q8_0 ~28.6 GB; LM Studio auto-indexes it). The GGUF is text-only; for the full multimodal + execution-verified system, self-host with vLLM as shown above.
+
+## FAQ
+
+**Is SwarmDo-A1 open source?** Yes — Apache-2.0, commercial use permitted. Weights, recipe, and full (including negative) results are public.
+
+**Can I run it on my own hardware?** Yes. Self-host with vLLM (adapter on Qwen3.6-27B), or run the quantized **GGUF** locally with Ollama / LM Studio / llama.cpp. Q4_K_M fits a single 24 GB GPU or a 32 GB Mac.
+
+**What is it based on?** A LoRA/PEFT adapter on **Qwen/Qwen3.6-27B** — a linear-attention hybrid (gated-DeltaNet) base with a vision tower. Apache-2.0.
+
+**Does it really do image-to-code?** Yes — it writes code from images (charts/plots/UI) and we verify it by *rendering the output and comparing to the target image* (an objective, reward-hackable-resistant signal), not by eyeballing.
+
+**How is it different from other open coding models?** SwarmDo-A1 is a *system*, not just a checkpoint: a strong open base **plus** an execution-verified best-of-N harness that runs the project's tests, **plus** an exec-grounded visual-coding capability. We report paired, held-out, execution-verified deltas — and publish the limitations.
+
+**Is it good at SWE-bench?** We report *relative, paired, held-out, execution-verified* wins (e.g. base + execution-verified selection solves 36 vs 24, p = 0.0005), not a single absolute leaderboard number we can't stand behind under paired testing.
+
+**What languages?** Python-centric agentic software engineering. It is a coding agent, not a general chat assistant.
+
+**Where are the full results?** Public hub: https://github.com/SwarmDo/models
+
+---
+
+*Topics: open source coding model · local LLM for coding · self-hosted AI coding assistant · agentic SWE-bench model · image to code / chart to code / screenshot to code · execution-verified code generation · Qwen3.6-27B LoRA · Ollama coding model · run a coding LLM locally · Apache-2.0 code model.*
+