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
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Download README.md from cloudqi/cqi_text_to_image_pt_v0: direct link, hf CLI and curl.
- Browser
- Download file 320 Bytes
-
https://huggingface.co/cloudqi/cqi_text_to_image_pt_v0/resolve/main/README.md
- Command line
-
hf download hf://cloudqi/cqi_text_to_image_pt_v0/README.md
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curl -L -o README.md https://huggingface.co/cloudqi/cqi_text_to_image_pt_v0/resolve/main/README.md
320 Bytes
metadata
license: creativeml-openrail-m
widget:
- text: |
Gato em alta qualidade na neve
tags:
- text-to-image
- stable-diffusion
language:
- pt
- en
Texto para Imagem - Base PT (From Anything MidJ)
Changelog
1. Modelo ajustado para adaptação à atualização do hugging
2. Otimizada entrada em pt/br