Instructions to use cloudqi/cqi_text_to_image_pt_v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cloudqi/cqi_text_to_image_pt_v0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cloudqi/cqi_text_to_image_pt_v0", dtype=torch.bfloat16, device_map="cuda") prompt = "Gato em alta qualidade na neve\n" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder/pytorch_model.bin from cloudqi/cqi_text_to_image_pt_v0: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/cloudqi/cqi_text_to_image_pt_v0/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://cloudqi/cqi_text_to_image_pt_v0/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/cloudqi/cqi_text_to_image_pt_v0/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 334ab0a188c3f89c220f48781b794095942d891024d7b3ae3e426987b131861c
- Size of remote file:
- 246 MB
- SHA256:
- 00f74197016019a736df3be12c32d4999f3055b6e759b6a7495f27c029da2d62
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