Instructions to use flow666/GSFixer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use flow666/GSFixer 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("flow666/GSFixer", 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: 873 Bytes
a13ee2c | 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 | {
"_class_name": "CogVideoXCrossTransformer3DModel",
"_diffusers_version": "0.32.2",
"activation_fn": "gelu-approximate",
"attention_bias": true,
"attention_head_dim": 64,
"dropout": 0.0,
"flip_sin_to_cos": true,
"freq_shift": 0,
"in_channels": 32,
"max_text_seq_length": 226,
"norm_elementwise_affine": true,
"norm_eps": 1e-05,
"num_attention_heads": 48,
"num_layers": 42,
"ofs_embed_dim": null,
"out_channels": 16,
"patch_bias": true,
"patch_size": 2,
"patch_size_t": null,
"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_learned_positional_embeddings": true,
"use_rotary_positional_embeddings": true
}
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