hospiz

Model overview

hospiz is published by jfreiter as a text-to-image LoRA. Hub tags record diffusers, flux, and lora with black-forest-labs/FLUX.1-dev as base model and adapter. According to the model card, it was trained on Replicate and uses HOSPIZ to trigger image generation.

Recorded capabilities

Use cases in the source record

• Text-to-image generation with FLUX.1-dev workflows that include the documented HOSPIZ trigger.
• Diffusers experiments that load lora.safetensors over the documented base model.

Limitations and unknowns

• No evaluation results were extracted from this record.
• No parameter count was extracted for this LoRA record.
• Provider state is historical snapshot data, not independently refreshed current availability.
• Training and style information comes from a brief publisher model card and has not been independently verified by Ethen.

Source and provenance

Source: jfreiter/hospiz

Captured: Unknown. Processed: 2026-09-07T19:35:23.709463+00:00.

Hospiz Trained on Replicate using: https://replicate.com/ostris/flux-dev-lora-trainer/train Trigger words You should use HOSPIZ 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( 'jfreiter/hospiz' , 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