Instructions to use h1t/oms_l_mixclip_xl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use h1t/oms_l_mixclip_xl with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("h1t/oms_l_mixclip_xl", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Update oms_module/config.json
Browse files- oms_module/config.json +1 -1
oms_module/config.json
CHANGED
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@@ -1,7 +1,7 @@
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{
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"_class_name": "UNet2DConditionWoCTModel",
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"_diffusers_version": "0.23.1",
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"_name_or_path": "oms_l_mixclip_xl",
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"act_fn": "silu",
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"attention_head_dim": [
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5,
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{
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"_class_name": "UNet2DConditionWoCTModel",
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"_diffusers_version": "0.23.1",
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+
"_name_or_path": "h1t/oms_l_mixclip_xl",
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"act_fn": "silu",
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"attention_head_dim": [
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5,
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