Instructions to use Guoyanjun/MemorizeWhenNeed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Guoyanjun/MemorizeWhenNeed with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Guoyanjun/MemorizeWhenNeed", 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
Upload 2 files
Browse files
camera_controlnet/config.json
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{
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"_class_name": "WanControlnet",
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"_diffusers_version": "0.37.0.dev0",
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"added_kv_proj_dim": null,
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"attention_head_dim": 128,
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"cross_attn_norm": true,
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"downscale_coef": 8,
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"eps": 1e-06,
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"ffn_dim": 8960,
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"freq_dim": 256,
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"hidden_channels": 36,
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"in_channels": 6,
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"num_attention_heads": 16,
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"num_layers": 8,
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"out_proj_dim": 5120,
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"patch_size": [
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1,
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2
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],
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"qk_norm": "rms_norm_across_heads",
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"rope_max_seq_len": 1024,
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"text_dim": 4096
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}
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camera_controlnet/diffusion_pytorch_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:de2b95409cde0ce05bffa2f99df96c3b047529c14e4034ae55fffc71639da187
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size 1111405800
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