Instructions to use rainbowow/AnimeColor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rainbowow/AnimeColor with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("rainbowow/AnimeColor", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
File size: 941 Bytes
524d341 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | {
"LFE_heads": 12,
"LFE_num_tokens": 32,
"LFE_output_dim": 2048,
"_class_name": "CogVideoXTransformer3DModel",
"_diffusers_version": "0.31.0",
"activation_fn": "gelu-approximate",
"add_noise_in_inpaint_model": false,
"attention_bias": true,
"attention_head_dim": 64,
"cross_attn_interval": 1,
"dropout": 0.0,
"flip_sin_to_cos": true,
"freq_shift": 0,
"in_channels": 32,
"is_train_qformer": true,
"max_text_seq_length": 226,
"norm_elementwise_affine": true,
"norm_eps": 1e-05,
"num_attention_heads": 30,
"num_layers": 30,
"out_channels": 16,
"patch_size": 2,
"qformer_scale": 1.0,
"sample_frames": 49,
"sample_height": 60,
"sample_width": 90,
"spatial_interpolation_scale": 1.875,
"temporal_compression_ratio": 4,
"temporal_interpolation_scale": 1.0,
"text_embed_dim": 4096,
"time_embed_dim": 512,
"timestep_activation_fn": "silu",
"use_rotary_positional_embeddings": false
}
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