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* docs: annotate hardcoded cuda device with alternatives in English docs * docs: annotate hardcoded device_map="cuda" with alternatives * update Signed-off-by: kaixuanliu <kaixuan.liu@intel.com> --------- Signed-off-by: kaixuanliu <kaixuan.liu@intel.com>
41 lines
1.3 KiB
Markdown
41 lines
1.3 KiB
Markdown
<!-- Copyright 2026 The HuggingFace Team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License. -->
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# Anima
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Anima is a text-to-image model that reuses the [`CosmosTransformer3DModel`] with a Qwen3 text encoder, a T5-token text conditioner, and the [`AutoencoderKLQwenImage`] VAE.
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```python
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import torch
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from diffusers import ModularPipeline
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pipe = ModularPipeline.from_pretrained("circlestone-labs/Anima-Base-v1.0-Diffusers")
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pipe.load_components(dtype=torch.bfloat16)
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pipe.to("cuda") # or "mps", "xpu", "cpu"
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image = pipe(prompt="masterpiece, best quality, 1girl, solo, city lights").images[0]
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```
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## AnimaModularPipeline
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[[autodoc]] AnimaModularPipeline
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## AnimaAutoBlocks
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[[autodoc]] AnimaAutoBlocks
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## AnimaTextConditioner
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[[autodoc]] AnimaTextConditioner
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