--- license: other license_name: flux-1-dev-non-commercial-license license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md language: - en tags: - flux - diffusers - lora - replicate base_model: black-forest-labs/FLUX.1-dev pipeline_tag: text-to-image instance_prompt: MLLW widget: - text: >- Generate an image of a humble scene in rural Thailand. In the center of the image, depict a man standing in front of a small, traditional Thai house with a thatched roof. The house should be simple, with wooden walls and a corrugated metal door. The thatched roof should be worn and slightly disheveled, with some straw or leaves sticking out. The MLLW with thin and lean ,long hair, The MLLW should be dressed in worn, earth-toned clothing, consisting of a loose-fitting farmer's shirt with buttons undone, revealing a plain white undershirt. His pants should be faded and patched in places, with a wide belt holding them up. He should wear scuffed and dusty boots that look like they've seen many years of hard work. The man's facial expression should be kind and weary, with deep lines etched on his face from years of working under the sun. He should have a gentle gaze, looking directly at the viewer with a sense of quiet dignity. output: url: images/example_psm220jkz.png --- # Mllw Trained on Replicate using: https://replicate.com/ostris/flux-dev-lora-trainer/train ## Trigger words You should use `MLLW` to trigger the image generation. ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers) ```py 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('BKKSPY/MLLW', 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](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)