Instructions to use wolfer45/reversedeepthroatv2-high-i2v-wan22 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wolfer45/reversedeepthroatv2-high-i2v-wan22 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ostris/wan22_i2v_14b_orbit_shot_lora", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("wolfer45/reversedeepthroatv2-high-i2v-wan22") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 626 Bytes
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tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/538277491_24622514807360171_6561907489047678575_n_crop.jpg
text: '-'
base_model: ostris/wan22_i2v_14b_orbit_shot_lora
instance_prompt: reversedeepthroatv2-high-i2v-wan22
---
# reversedeepthroatv2-high-i2v-wan22
<Gallery />
## Model description
reversedeepthroatv2-high-i2v-wan22
## Trigger words
You should use `reversedeepthroatv2-high-i2v-wan22` to trigger the image generation.
## Download model
[Download](/wolfer45/reversedeepthroatv2-high-i2v-wan22/tree/main) them in the Files & versions tab.
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