Instructions to use Avener/AVeneR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Avener/AVeneR with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Avener/AVeneR", dtype=torch.bfloat16, device_map="cuda") prompt = "My name is Julien and I like to" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
| license: artistic-2.0 | |
| datasets: | |
| - k-mktr/improved-flux-prompts-photoreal-portrait | |
| language: | |
| - en | |
| metrics: | |
| - bleurt | |
| base_model: | |
| - ostris/OpenFLUX.1 | |
| new_version: black-forest-labs/FLUX.1-dev | |
| pipeline_tag: text-generation | |
| library_name: diffusers | |
| tags: | |
| - art | |