Text-to-Image
Diffusers
Safetensors
llama
dfloat11
df11
lossless compression
70% size, 100% accuracy
Instructions to use DFloat11/FLUX.1-Depth-dev-DF11 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DFloat11/FLUX.1-Depth-dev-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("DFloat11/FLUX.1-Depth-dev-DF11", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 767 Bytes
bbd8d9a | 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 37 | {
"dfloat11_config": {
"bytes_per_thread": 8,
"pattern_dict": {
"transformer_blocks.\\d+": [
"norm1.linear",
"norm1_context.linear",
"attn.to_q",
"attn.to_k",
"attn.to_v",
"attn.add_k_proj",
"attn.add_v_proj",
"attn.add_q_proj",
"attn.to_out.0",
"attn.to_add_out",
"ff.net.0.proj",
"ff.net.2",
"ff_context.net.0.proj",
"ff_context.net.2"
],
"single_transformer_blocks.\\d+": [
"norm.linear",
"proj_mlp",
"proj_out",
"attn.to_q",
"attn.to_k",
"attn.to_v"
]
},
"threads_per_block": [
512
],
"version": "0.2.0"
},
"model_type": "llama"
}
|