Add post-training folder

post-training/README.md

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+# Screencoder Train: MLLM SFT + RL Training Stack
+
+This repo combines supervised fine-tuning (SFT) via `LLaMA-Factory` and reinforcement learning (GRPO) via `VLM-R1`, plus a minimal vLLM serving setup.
+
+## Contents
+- `LLaMA-Factory/`: general SFT for LLM/VLM and evaluation
+- `VLM-R1/`: RL training (GRPO) for VLM tasks like REC/OVD/Math
+- `vllm/`: minimal scripts for OpenAI-style API with vLLM
+- `conda_envs/`: example conda env YAMLs and optional env archives
+- `scripts/`: convenience wrappers
+
+## Quickstart
+
+0) Optional bootstrap
+```bash
+bash scripts/bootstrap_envs.sh         # installs rl, vllm, data, sft
+```
+
+1) Environments
+```bash
+# Option A: from YAMLs (recommended to customize as needed)
+conda env create -f conda_envs/sft_env.yml
+conda env create -f conda_envs/rl_env.yml
+# Optional: a separate env for vLLM
+conda create -n vllm python=3.10 -y
+```
+
+2) Data
+- SFT: see `LLaMA-Factory/data/get_data.sh` and `LLaMA-Factory/data/dataset_info.json`.
+- RL: follow dataset links in `VLM-R1/README.md` (COCO, RefCOCO/+/g, LISA-Grounding, etc.).
+
+3) Train
+```bash
+# SFT (LoRA example)
+conda activate sft
+bash scripts/run_sft.sh LLaMA-Factory/examples/train_lora/llama3_lora_sft.yaml
+
+# RL (REC GRPO example)
+conda activate rl
+bash scripts/run_rl.sh VLM-R1/run_scripts/run_grpo_rec.sh
+```
+
+4) Inference (OpenAI-style API via vLLM)
+```bash
+conda activate vllm
+bash scripts/run_vllm.sh LLaMA-Factory/examples/inference/llama3_vllm.yaml 8000
+```
+
+- Test clients in `LLaMA-Factory/scripts/api_example/`.
+
+## Notes
+- Upstream project docs remain authoritative:
+  - LLaMA-Factory: see its `README.md` and `examples/` for many model/task recipes.
+  - VLM-R1: see its `README.md` and `run_scripts/` for GRPO variants, multi-node, LoRA.
+- Large assets (data, checkpoints, env tar parts) are ignored via `.gitignore` by default.
+
+## License
+- Each subproject keeps its own license. Follow model/checkpoint licenses accordingly.
+
+## Acknowledgements
+- This project builds upon and thanks the following open-source efforts:
+  - LLaMA-Factory: https://github.com/hiyouga/LLaMA-Factory
+  - VLM-R1: https://github.com/om-ai-lab/VLM-R1
+