Instructions to use nvidia/Cosmos3-Super-Text2Image-4Step with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Cosmos
How to use nvidia/Cosmos3-Super-Text2Image-4Step with Cosmos:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
File size: 677 Bytes
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"_class_name": "FlowMatchEulerDiscreteScheduler",
"_diffusers_version": "0.39.0",
"base_image_seq_len": 256,
"base_shift": 0.5,
"fixed_step_requires_explicit_sigmas": true,
"fixed_step_sampler_config": {
"sample_type": "sde",
"t_list": [
1.0,
0.9375,
0.8333333333333334,
0.625
]
},
"invert_sigmas": false,
"max_image_seq_len": 4096,
"max_shift": 1.15,
"num_train_timesteps": 1000,
"shift": 1.0,
"shift_terminal": null,
"stochastic_sampling": true,
"time_shift_type": "exponential",
"use_beta_sigmas": false,
"use_dynamic_shifting": false,
"use_exponential_sigmas": false,
"use_karras_sigmas": false
}
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