metadata
base_model: CompVis/stable-diffusion-v1-4
library_name: diffusers
license: creativeml-openrail-m
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
- diffusers-training
- lora
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
- diffusers-training
inference: true
LoRA text2image fine-tuning - arnaudstiegler/sd-model-gameNgen
These are LoRA adaption weights for CompVis/stable-diffusion-v1-4. The weights were fine-tuned on the arnaudstiegler/gameNgen_test_dataset dataset. You can find some example images in the following.
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
Command:
python train_text_to_image.py --dataset_name P-H-B-D-a16z/ViZDoom-Deathmatch-PPO-Lrg --gradient_checkpointing --learning_rate 5e-5 --train_batch_size 8 --num_train_epochs 10 --validation_steps 250 --output_dir sd-model-finetune --push_to_hub --report_to wandb