Update README.md

README.md

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----
-license: mit
----
+---
+base_model: XD-MU/ScriptAgent
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:XD-MU/ScriptAgent
+- lora
+- transformers
+---
+
+
+# ScriptAgent: Dialogue-to-Shooting-Script Generation Model
+
+This model is a fine-tuned adapter (LoRA) on top of the `XD-MU/ScriptAgent` base model, designed to **generate detailed shooting scripts from dialogue inputs**. It is trained to transform conversational text into structured screenplay formats suitable for film or video production.
+
+The model is compatible with [ms-swift](https://github.com/modelscope/swift) and supports efficient inference via the **vLLM backend**.
+
+> 💡 Note: This repository contains a **PEFT adapter** (e.g., LoRA). To use it, you must merge it with the original base model or load it via `ms-swift`.
+
+## ▶️ Inference with ms-swift (vLLM Backend)
+
+To generate shooting scripts from dialogue inputs, use the following command with **ms-swift**:
+
+You can find **DialoguePrompts** here: https://huggingface.co/datasets/XD-MU/DialoguePrompts
+```bash
+import os
+from huggingface_hub import snapshot_download
+from swift.llm import PtEngine, RequestConfig, InferRequest
+os.environ['CUDA_VISIBLE_DEVICES'] = '0'
+
+model_name = "XD-MU/ScriptAgent"
+local_path = "./models/ScriptAgent"
+
+snapshot_download(
+    repo_id=model_name,
+    local_dir=local_path,
+    local_dir_use_symlinks=False, 
+    resume_download=True 
+)
+
+engine = PtEngine(local_path, max_batch_size=1)
+request_config = RequestConfig(max_tokens=8192, temperature=0.7)
+
+infer_request = InferRequest(messages=[
+    {"role": "user", "content": "Your Dialogue"}
+])
+response = engine.infer([infer_request], request_config)[0]
+
+print(response.choices[0].message.content)
+```
+
+