Text-to-Image
Diffusers
Safetensors
ErnieImagePipeline
ernie-image
sdnq
quantized
uint4
static
quantized-matmul
Instructions to use WaveCut/ERNIE-Image-Turbo-SDNQ-uint4-static with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/ERNIE-Image-Turbo-SDNQ-uint4-static with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("WaveCut/ERNIE-Image-Turbo-SDNQ-uint4-static", 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: 408 Bytes
f2b7557 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"add_prefix_space": null,
"backend": "tokenizers",
"bos_token": "<s>",
"clean_up_tokenization_spaces": false,
"eos_token": "</s>",
"is_local": true,
"legacy": true,
"local_files_only": false,
"model_max_length": 2048,
"pad_token": "<pad>",
"processor_class": "PixtralProcessor",
"tokenizer_class": "TokenizersBackend",
"unk_token": "<unk>",
"use_default_system_prompt": false
}
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