Instructions to use Muhammadreza/generative-metaverse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muhammadreza/generative-metaverse with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muhammadreza/generative-metaverse") prompt = "a coffee machine, generative_meta4" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
generative-metaverse
Model trained with AI Toolkit by Ostris

- Prompt
- a coffee machine, generative_meta4

- Prompt
- a hamburger, generative_meta4
Trigger words
You should use generative_meta4 to trigger the image generation.
Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, etc.
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Use it with the 🧨 diffusers library
from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('Muhammadreza/generative-metaverse', weight_name='generative-metaverse.safetensors')
image = pipeline('a coffee machine, generative_meta4').images[0]
image.save("my_image.png")
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
- Downloads last month
- 18
Model tree for Muhammadreza/generative-metaverse
Base model
black-forest-labs/FLUX.1-dev