Upload folder using ModelScope SDK (batch 1/1)

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Cherrytest
2025-11-27 04:36:56 +00:00
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*.zst filter=lfs diff=lfs merge=lfs -text *.zst filter=lfs diff=lfs merge=lfs -text
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split_files/text_encoders/qwen_3_4b.safetensors filter=lfs diff=lfs merge=lfs -text
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--- ---
license: Apache License 2.0 tags:
tags: [] - diffusion-single-file
- comfyui
#model-type:
##如 gpt、phi、llama、chatglm、baichuan 等
#- gpt
#domain:
##如 nlp、cv、audio、multi-modal
#- nlp
#language:
##语言代码列表 https://help.aliyun.com/document_detail/215387.html?spm=a2c4g.11186623.0.0.9f8d7467kni6Aa
#- cn
#metrics:
##如 CIDEr、Blue、ROUGE 等
#- CIDEr
#tags:
##各种自定义,包括 pretrained、fine-tuned、instruction-tuned、RL-tuned 等训练方法和其他
#- pretrained
#tools:
##如 vllm、fastchat、llamacpp、AdaSeq 等
#- vllm
--- ---
### 当前模型的贡献者未提供更加详细的模型介绍。模型文件和权重,可浏览“模型文件”页面获取。
#### 您可以通过如下git clone命令或者ModelScope SDK来下载模型
SDK下载 Workflows: https://comfyanonymous.github.io/ComfyUI_examples/z_image/
```bash
#安装ModelScope
pip install modelscope
```
```python
#SDK模型下载
from modelscope import snapshot_download
model_dir = snapshot_download('Comfy-Org/z_image_turbo')
```
Git下载
```
#Git模型下载
git clone https://www.modelscope.cn/Comfy-Org/z_image_turbo.git
```
<p style="color: lightgrey;">如果您是本模型的贡献者,我们邀请您根据<a href="https://modelscope.cn/docs/ModelScope%E6%A8%A1%E5%9E%8B%E6%8E%A5%E5%85%A5%E6%B5%81%E7%A8%8B%E6%A6%82%E8%A7%88" style="color: lightgrey; text-decoration: underline;">模型贡献文档</a>,及时完善模型卡片内容。</p>

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{"framework": "pytorch", "task": "text-to-image-synthesis", "allow_remote": true}

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import safetensors.torch
import torch
import sys
# Usage: python z_image_convert_original_to_comfy.py output.safetensors diffusion_model*.safetensors
cast_to = None
if "fp8_e4m3fn" in sys.argv[1]:
cast_to = torch.float8_e4m3fn
elif "fp16" in sys.argv[1]:
cast_to = torch.float16
elif "bf16" in sys.argv[1]:
cast_to = torch.bfloat16
replace_keys = {"all_final_layer.2-1.": "final_layer.",
"all_x_embedder.2-1.": "x_embedder.",
".attention.to_out.0.bias": ".attention.out.bias",
".attention.norm_k.weight": ".attention.k_norm.weight",
".attention.norm_q.weight": ".attention.q_norm.weight",
".attention.to_out.0.weight": ".attention.out.weight"
}
out_sd = {}
for f in sys.argv[2:]:
sd = safetensors.torch.load_file(f)
cc = None
for k in sd:
w = sd[k]
if cast_to is not None:
w = w.to(cast_to)
k_out = k
if k_out.endswith(".attention.to_out.0.bias"):
continue
if k_out.endswith(".attention.to_k.weight"):
cc = [w]
continue
if k_out.endswith(".attention.to_q.weight"):
cc = [w] + cc
continue
if k_out.endswith(".attention.to_v.weight"):
cc = cc + [w]
w = torch.cat(cc, dim=0)
k_out = k_out.replace(".attention.to_v.weight", ".attention.qkv.weight")
for r, rr in replace_keys.items():
k_out = k_out.replace(r, rr)
out_sd[k_out] = w
safetensors.torch.save_file(out_sd, sys.argv[1])