weathon/anti_aesthetics_lora_flux_nf4

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Flux DreamBooth LoRA - weathon/antiaestheticslorafluxnf4

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Model description

These are weathon/antiaestheticslorafluxnf4 DreamBooth LoRA weights for black-forest-labs/FLUX.1-dev.

The weights were trained using DreamBooth with the Flux diffusers trainer.

Was LoRA for the text encoder enabled? False.

Quantization config:

BitsAndBytesConfig {
  "_load_in_4bit": true,
  "_load_in_8bit": false,
  "bnb_4bit_compute_dtype": "float16",
  "bnb_4bit_quant_storage": "uint8",
  "bnb_4bit_quant_type": "nf4",
  "bnb_4bit_use_double_quant": false,
  "llm_int8_enable_fp32_cpu_offload": false,
  "llm_int8_has_fp16_weight": false,
  "llm_int8_skip_modules": null,
  "llm_int8_threshold": 6.0,
  "load_in_4bit": true,
  "load_in_8bit": false,
  "quant_method": "bitsandbytes"
}

Trigger words

You should use None to trigger the image generation.

Download model

Download the *.safetensors LoRA in the Files & versions tab.

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

Usage

TODO

License

Please adhere to the licensing terms as described here.

Intended uses & limitations

How to use

# TODO: add an example code snippet for running this diffusion pipeline

Limitations and bias

[TODO: provide examples of latent issues and potential remediations]

Training details

[TODO: describe the data used to train the model]