Instructions to use ZaneSFL/zh-ppt-voice-agent-model-lora-support-interrupt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ZaneSFL/zh-ppt-voice-agent-model-lora-support-interrupt with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-4B-Instruct-2507") model = PeftModel.from_pretrained(base_model, "ZaneSFL/zh-ppt-voice-agent-model-lora-support-interrupt") - Notebooks
- Google Colab
- Kaggle
zh-ppt-voice-agent-model-lora-support-interrupt
Base: Qwen/Qwen3-4B-Instruct-2507
PEFT: QLoRA,中文 PPT 语音助手多轮对话(含 TTS 插话场景下的应答)。
related works:
- https://huggingface.co/datasets/ZaneSFL/zh-ppt-voice-agent-interrupt-dialogues
- https://github.com/ZHYsfl/EducationAgent
Load
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
base = "Qwen/Qwen3-4B-Instruct-2507"
adapter = "ZaneSFL/zh-ppt-voice-agent-model-lora-support-interrupt"
tokenizer = AutoTokenizer.from_pretrained(adapter, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
base, torch_dtype="auto", device_map="auto", trust_remote_code=True
)
model = PeftModel.from_pretrained(model, adapter)
按 Qwen Instruct 的 messages + apply_chat_template 推理即可。
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Base model
Qwen/Qwen3-4B-Instruct-2507