--- license: creativeml-openrail-m library_name: diffusers tags: - stable-diffusion - stable-diffusion-diffusers - text-to-image - diffusers - diffusers-training - lora - stable-diffusion - stable-diffusion-diffusers - text-to-image - diffusers - diffusers-training - lora base_model: stabilityai/stable-diffusion-2-1 inference: true --- # LoRA text2image fine-tuning - remi349/sd_trained_3D_lora These are LoRA adaption weights are for stabilityai/stable-diffusion-2-1. The weights were fine-tuned on the remi349/finetuning_dataset_for_3D_training dataset thanks to the library [diffusers](https://github.com/huggingface/diffusers/blob/main/examples/text_to_image/train_text_to_image_lora.py). ## Intended uses & limitations This model aims at generating images of isolated objects, compatible with 2D_to_3D models like [Triposr](https://github.com/VAST-AI-Research/TripoSR) or [CRM](https://huggingface.co/Zhengyi/CRM). It was finetuned in order to create after a pipeline of prompt-to-3D model. #### How to use ```python # First load the basic architecture and everything import torch from diffusers import StableDiffusionPipeline pipe = StableDiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1", torch_dtype=torch.float16) # Then add the lora weights to the model stable diffusion 2 pipe.unet.load_attn_procs('ACROSS-Lab/sd_finetuned') pipe.to("cuda") # Then you can begin the inference process on a prompt and save the image generated prompt = 'a rabbit with a yellow jacket' image = pipe(prompt, num_inference_steps=30, guidance_scale=7.5).images[0] image.save("my_image.png") ``` #### Limitations and bias This model is a first try some hyperparameters tuning should be done, but for that we would need a solid automated benchmark. ## Training details The model finetuned model is [Stable Diffusion 2](https://huggingface.co/stabilityai/stable-diffusion-2). The data used to train this model is the dataset available on uggingface at 'remi349/finetuning_dataset_for_3D_training'. you can download it thanks to the command ```python from datasets import load_dataset dataset = load_dataset("ACROSS_Lab/finetuning_sd_dataset_objaverse", split = 'train') ``` This dataset is a subset of the dataset [Objaverse](https://objaverse.allenai.org/). ## Collaboration This model and dataset has been made in collaboration by [Josué ADOSSEHOUN](https://huggingface.co/josh007) and [Rémi DUCOTTET](https://huggingface.co/remi349)