Instructions to use Danielbsittler/wanhigh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Danielbsittler/wanhigh 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", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Danielbsittler/wanhigh") prompt = "ASCII\u0000\u0000\u0000Screenshot" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Browse files
6576853d-1cdb-4eea-a0a7-11cfbe859c9a-u1_t2v_A14B_separate_high_noise_lora_81da6b10-2366-47ac-aa09-a65645885cdd.safetensors.zip
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version https://git-lfs.github.com/spec/v1
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oid sha256:ed259857e859f39e91fdf85717a1ce1f15185ccfda6fbbf59dfbf6f3a2021e29
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size 212100901
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images/IMG_1672.jpeg
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Git LFS Details
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