Instructions to use AXERA-TECH/lcm-lora-sdv1-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AXERA-TECH/lcm-lora-sdv1-5 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AXERA-TECH/lcm-lora-sdv1-5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
yongqiang commited on
Commit ·
d6a657f
1
Parent(s): 63c4ef7
update version of dependent lib
Browse files- README.md +1 -0
- requirements.txt +6 -4
README.md
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@@ -70,6 +70,7 @@ pip install -r requirements.txt
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```sh
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pip3 install gradio==5.42.0
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python3 gradio_demo.py --model_dir models --isize 512x512
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```
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```sh
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pip3 install gradio==5.42.0
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pip3 install huggingface-hub==0.34.4
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python3 gradio_demo.py --model_dir models --isize 512x512
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```
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requirements.txt
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protobuf==3.20.3
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onnx==1.16.0
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onnxsim==0.4.36
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torch==2.1.
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transformers==4.45.0
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peft
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diffusers
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numpy==1.
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protobuf==3.20.3
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onnx==1.16.0
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onnxsim==0.4.36
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torch==2.1.0
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torchvision==0.16.0
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torchaudio==2.1.0
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transformers==4.45.0
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peft==0.13.1
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diffusers==0.29.0
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numpy==1.23.5
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