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---
title: ZeroGPU
emoji: 🖼
colorFrom: purple
colorTo: red
sdk: gradio
sdk_version: 5.25.2
app_file: app.py
pinned: false
license: apache-2.0
---
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
commands:
pip install git+https://github.com/huggingface/diffusers
accelerate launch \
--deepspeed_config_file ds_config.json \
diffusers/examples/dreambooth/train_dreambooth.py \
--pretrained_model_name_or_path="runwayml/stable-diffusion-v1-5" \
--instance_data_dir="./nyc_ads_dataset" \
--instance_prompt="a photo of an urbanad nyc" \
--output_dir="./nyc-ad-model" \
--resolution=100 \
--train_batch_size=1 \
--gradient_accumulation_steps=1 \
--gradient_checkpointing \
--learning_rate=5e-6 \
--lr_scheduler="constant" \
--lr_warmup_steps=0 \
--max_train_steps=400 \
--mixed_precision="fp16" \
--checkpointing_steps=100 \
--checkpoints_total_limit=1 \
--report_to="tensorboard" \
--logging_dir="./nyc-ad-model/logs"
fine tune a trained model: --pretrained_model_name_or_path="./nyc-ad-model/checkpoint-400" \
export PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True
import torch
torch.cuda.empty_cache()
torch.cuda.reset_peak_memory_stats()
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# 1 Fine‑tune image model LoRA+QLoRA
accelerate launch --deepspeed_config_file=ds_config_zero3.json train_lora.py
python train_lora.py
# 2 SFT 语言模型
python sft_train.py
# 3 Build RAG index
python build_embeddings.py
# 4 (可选) 收集偏好 → 训练 reward model
python reward_model.py
# 5 PPO RLHF 微调
python ppo_tune.py
# 6 Inference with RAG
python rag_infer.py |