metadata
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 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
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)