Inference Providersfor perspectable/potra-800-flux

from huggingface_hub import InferenceClient

client = InferenceClient(
    provider="hf-inference",
    api_key="hf_xxxxxxxxxxxxxxxxxxxxxxxx",
)

# output is a PIL.Image object
image = client.text_to_image(
	"Astronaut riding a horse",
	model="perspectable/potra-800-flux",
)

Quick Links

Potra 800 Flux

Trained on Replicate using:

https://replicate.com/ostris/flux-dev-lora-trainer/train

Trigger words

You should use TOK to trigger the image generation.

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.float16).to('cuda')
pipeline.load_lora_weights('perspectable/potra-800-flux', weight_name='lora.safetensors')
image = pipeline('your prompt').images[0]

For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers

perspectable
/

potra-800-flux

Potra 800 Flux

Trigger words

Use it with the 🧨 diffusers library

Model tree for perspectable/potra-800-flux