jiangzeyinzi
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Commit
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Browse files- 0_SwiftLoRA/adapter_config.json +34 -0
- 0_SwiftLoRA/adapter_model.bin +3 -0
- README.md +168 -0
- configuration.json +1 -0
- image.jpg +0 -0
- params.yaml +34 -0
0_SwiftLoRA/adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": null,
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"bias": "none",
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"enable_lora": null,
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"fan_in_fan_out": false,
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"inference_mode": false,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 64,
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"lora_dropout": 0.0,
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"lora_dtype": null,
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"lorap_emb_lr": 1e-06,
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"lorap_lr_ratio": 16.0,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"model_key_mapping": null,
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 64,
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"rank_pattern": {},
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"revision": null,
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"swift_type": "LORA",
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"target_modules": "(cond_stage_model.*(q_proj|k_proj|v_proj|out_proj|mlp.fc1|mlp.fc2))|(model.*(to_q|to_k|to_v|to_out.0|net.0.proj|net.2))$",
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"task_type": null,
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"use_dora": false,
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"use_merged_linear": false,
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"use_qa_lora": false,
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"use_rslora": false
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}
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0_SwiftLoRA/adapter_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:e8f7627401d1372d0ed3d183d498fd97fedcc9d2672ff244e1642591ea3c7dc8
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size 138393741
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README.md
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---
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frameworks:
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- Pytorch
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license: apache-2.0
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tasks:
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- efficient-diffusion-tuning
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---
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<p align="center">
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<h2 align="center">SD15-TEXT_LORA-3DStyle-20240523-test</h2>
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<p align="center">
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<br>
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<a href="https://github.com/modelscope/scepter/"><img src="https://img.shields.io/badge/powered by-scepter-6FEBB9.svg"></a>
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<br>
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</p>
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## Model Introduction
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test123
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## Model Parameters
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<table>
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<thead>
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<tr>
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<th rowspan="2">Base Model</th>
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<th rowspan="2">Tuner Type</th>
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<th colspan="4">Training Parameters</th>
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</tr>
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<tr>
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<th>Batch Size</th>
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<th>Epochs</th>
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<th>Learning Rate</th>
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<th>Resolution</th>
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</tr>
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</thead>
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<tbody align="center">
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<tr>
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<td rowspan="8">SD1.5</td>
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<td>TEXT_LORA</td>
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<td>4</td>
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<td>50</td>
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<td>0.0001</td>
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<td>[512, 512]</td>
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</tr>
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</tbody>
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</table>
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<table>
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<thead>
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<tr>
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<th>Data Type</th>
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<th>Data Space</th>
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<th>Data Name</th>
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<th>Data Subset</th>
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</tr>
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</thead>
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<tbody align="center">
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<tr>
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<td>Dataset zip</td>
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<td></td>
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<td>/home/scepter/cache/scepter_ui/datasets/scepter_txt2img_3D_example</td>
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<td>default</td>
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</tr>
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</tbody>
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</table>
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## Model Performance
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Given the input "a boy wearing a jacket," the following image may be generated:
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![image](./image.jpg)
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## Model Usage
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### Command Line Execution
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* Run using Scepter's SDK, taking care to use different configuration files in accordance with the different base models, as per the corresponding relationships shown below
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<table>
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<thead>
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<tr>
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<th rowspan="2">Base Model</th>
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<th rowspan="1">LORA</th>
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<th colspan="1">SCE</th>
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<th colspan="1">TEXT_LORA</th>
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<th colspan="1">TEXT_SCE</th>
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</tr>
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</thead>
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<tbody align="center">
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<tr>
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<td rowspan="8">SD1.5</td>
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<td><a href="https://github.com/modelscope/scepter/blob/main/scepter/methods/examples/generation/stable_diffusion_1.5_512_lora.yaml">lora_cfg</a></td>
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<td><a href="https://github.com/modelscope/scepter/blob/main/scepter/methods/scedit/t2i/sd15_512_sce_t2i_swift.yaml">sce_cfg</a></td>
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<td><a href="https://github.com/modelscope/scepter/blob/main/scepter/methods/examples/generation/stable_diffusion_1.5_512_text_lora.yaml">text_lora_cfg</a></td>
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<td><a href="https://github.com/modelscope/scepter/blob/main/scepter/methods/scedit/t2i/stable_diffusion_1.5_512_text_sce.yaml">text_sce_cfg</a></td>
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</tr>
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</tbody>
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<tbody align="center">
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<tr>
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<td rowspan="8">SD2.1</td>
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<td><a href="https://github.com/modelscope/scepter/blob/main/scepter/methods/examples/generation/stable_diffusion_2.1_768_lora.yaml">lora_cfg</a></td>
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<td><a href="https://github.com/modelscope/scepter/blob/main/scepter/methods/scedit/t2i/sd21_768_sce_t2i_swift.yaml">sce_cfg</a></td>
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<td><a href="https://github.com/modelscope/scepter/blob/main/scepter/methods/examples/generation/stable_diffusion_2.1_768_text_lora.yaml">text_lora_cfg</a></td>
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<td><a href="https://github.com/modelscope/scepter/blob/main/scepter/methods/scedit/t2i/sd21_768_text_sce_t2i_swift.yaml">text_sce_cfg</a></td>
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</tr>
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</tbody>
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<tbody align="center">
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<tr>
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<td rowspan="8">SDXL</td>
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<td><a href="https://github.com/modelscope/scepter/blob/main/scepter/methods/examples/generation/stable_diffusion_xl_1024_lora.yaml">lora_cfg</a></td>
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<td><a href="https://github.com/modelscope/scepter/blob/main/scepter/methods/scedit/t2i/sdxl_1024_sce_t2i_swift.yaml">sce_cfg</a></td>
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<td><a href="https://github.com/modelscope/scepter/blob/main/scepter/methods/examples/generation/stable_diffusion_xl_1024_text_lora.yaml">text_lora_cfg</a></td>
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<td><a href="https://github.com/modelscope/scepter/blob/main/scepter/methods/scedit/t2i/sdxl_1024_text_sce_t2i_swift.yaml">text_sce_cfg</a></td>
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</tr>
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</tbody>
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</table>
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* Running from Source Code
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```shell
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git clone https://github.com/modelscope/scepter.git
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cd scepter
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pip install -r requirements/recommended.txt
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PYTHONPATH=. python scepter/tools/run_inference.py
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--pretrained_model {this model folder}
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--cfg {lora_cfg} or {sce_cfg} or {text_lora_cfg} or {text_sce_cfg}
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--prompt 'a boy wearing a jacket'
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--save_folder 'inference'
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```
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* Running after Installing Scepter (Recommended)
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```shell
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pip install scepter
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python -m scepter/tools/run_inference.py
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--pretrained_model {this model folder}
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--cfg {lora_cfg} or {sce_cfg} or {text_lora_cfg} or {text_sce_cfg}
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--prompt 'a boy wearing a jacket'
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--save_folder 'inference'
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```
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### Running with Scepter Studio
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```shell
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pip install scepter
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# Launch Scepter Studio
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python -m scepter.tools.webui
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```
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* Refer to the following guides for model usage.
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(video url)
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## Model Reference
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If you wish to use this model for your own purposes, please cite it as follows.
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```bibtex
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@misc{SD15-TEXT_LORA-3DStyle-20240523-test,
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title = {SD15-TEXT_LORA-3DStyle-20240523-test, https://huggingface.co/jiangzeyinzi/SD15-TEXT_LORA-3DStyle-20240523-test},
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author = {jiangzeyinzi},
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year = {2024}
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}
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```
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This model was trained using [Scepter Studio](https://github.com/modelscope/scepter); [Scepter](https://github.com/modelscope/scepter)
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is an algorithm framework and toolbox developed by the Alibaba Tongyi Wanxiang Team. It provides a suite of tools and models for image generation, editing, fine-tuning, data processing, and more. If you find our work beneficial for your research,
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please cite as follows.
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```bibtex
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@misc{scepter,
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title = {SCEPTER, https://github.com/modelscope/scepter},
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author = {SCEPTER},
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year = {2023}
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}
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```
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configuration.json
ADDED
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{}
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image.jpg
ADDED
params.yaml
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DESCRIPTION: test123
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PARAMS:
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base_model: stable_diffusion
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base_model_revision: SD1.5
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bucket_no_upscale: false
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bucket_resolution_steps: 64.0
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data_type: Dataset zip
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enable_resolution_bucket: false
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eval_prompts:
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- a boy wearing a jacket
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- a dog running on the lawn
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learning_rate: 0.0001
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lora_alpha: 64.0
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lora_rank: 64.0
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max_bucket_resolution: 1024.0
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min_bucket_resolution: 256.0
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ms_data_name: /home/scepter/cache/scepter_ui/datasets/scepter_txt2img_3D_example
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ms_data_space: ''
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ms_data_subname: default
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ori_data_name: 3D_example
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prompt_prefix: ''
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push_to_hub: false
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replace_keywords: ''
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resolution_height: 512
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resolution_width: 512
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save_interval: 25
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sce_ratio: 1
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text_lora_alpha: 256.0
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text_lora_rank: 256.0
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train_batch_size: 4
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train_epoch: 50
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tuner_name: TEXT_LORA
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work_dir: ''
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work_name: ''
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