Instructions to use mingyi456/ERNIE-Image-Turbo-DF11 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mingyi456/ERNIE-Image-Turbo-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/ERNIE-Image-Turbo-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/ERNIE-Image-Turbo-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
Upload 2 files
Browse files- config.json +26 -0
- model.safetensors +3 -0
config.json
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{
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"dfloat11_config": {
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"version": "0.5.0",
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"threads_per_block": [
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512
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],
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"bytes_per_thread": 8,
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"pattern_dict": {
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"time_embedding": [
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"linear_1",
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"linear_2"
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],
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"adaLN_modulation.1": [],
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"layers\\.\\d+": [
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"self_attention.to_q",
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"self_attention.to_k",
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"self_attention.to_v",
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"self_attention.to_out.0",
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"mlp.gate_proj",
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"mlp.up_proj",
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"mlp.linear_fc2"
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],
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"final_norm.linear": []
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}
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}
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:cb978808d96bbb7b5debbbeb00a1bb3888cc104571c1d39de36e8033bf189fd7
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size 10922771783
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