Instructions to use mingyi456/Cosmos-Predict2-2B-Text2Image-DF11 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mingyi456/Cosmos-Predict2-2B-Text2Image-DF11 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mingyi456/Cosmos-Predict2-2B-Text2Image-DF11", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Diffusion Single File
How to use mingyi456/Cosmos-Predict2-2B-Text2Image-DF11 with Diffusion Single File:
# 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
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 697 Bytes
db6a5c9 | 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 | {
"dfloat11_config": {
"version": "0.5.0",
"threads_per_block": [
512
],
"bytes_per_thread": 8,
"pattern_dict": {
"transformer_blocks\\.\\d+": [
"norm1.linear_1",
"norm1.linear_2",
"attn1.to_q",
"attn1.to_k",
"attn1.to_v",
"attn1.to_out.0",
"norm2.linear_1",
"norm2.linear_2",
"attn2.to_q",
"attn2.to_k",
"attn2.to_v",
"attn2.to_out.0",
"norm3.linear_1",
"norm3.linear_2",
"ff.net.0.proj",
"ff.net.2"
],
"time_embed\\.t_embedder": [
"linear_1",
"linear_2"
]
}
}
} |