Instructions to use hongrui/mammogram_v_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hongrui/mammogram_v_2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("hongrui/mammogram_v_2") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
End of training
Browse filesThis view is limited to 50 files because it contains too many changes. See raw diff
- README.md +21 -0
- checkpoint-100/optimizer.bin +3 -0
- checkpoint-100/pytorch_model.bin +3 -0
- checkpoint-100/random_states_0.pkl +3 -0
- checkpoint-100/scaler.pt +3 -0
- checkpoint-100/scheduler.bin +3 -0
- checkpoint-1000/optimizer.bin +3 -0
- checkpoint-1000/pytorch_model.bin +3 -0
- checkpoint-1000/random_states_0.pkl +3 -0
- checkpoint-1000/scaler.pt +3 -0
- checkpoint-1000/scheduler.bin +3 -0
- checkpoint-1100/optimizer.bin +3 -0
- checkpoint-1100/pytorch_model.bin +3 -0
- checkpoint-1100/random_states_0.pkl +3 -0
- checkpoint-1100/scaler.pt +3 -0
- checkpoint-1100/scheduler.bin +3 -0
- checkpoint-1200/optimizer.bin +3 -0
- checkpoint-1200/pytorch_model.bin +3 -0
- checkpoint-1200/random_states_0.pkl +3 -0
- checkpoint-1200/scaler.pt +3 -0
- checkpoint-1200/scheduler.bin +3 -0
- checkpoint-1300/optimizer.bin +3 -0
- checkpoint-1300/pytorch_model.bin +3 -0
- checkpoint-1300/random_states_0.pkl +3 -0
- checkpoint-1300/scaler.pt +3 -0
- checkpoint-1300/scheduler.bin +3 -0
- checkpoint-1400/optimizer.bin +3 -0
- checkpoint-1400/pytorch_model.bin +3 -0
- checkpoint-1400/random_states_0.pkl +3 -0
- checkpoint-1400/scaler.pt +3 -0
- checkpoint-1400/scheduler.bin +3 -0
- checkpoint-1500/optimizer.bin +3 -0
- checkpoint-1500/pytorch_model.bin +3 -0
- checkpoint-1500/random_states_0.pkl +3 -0
- checkpoint-1500/scaler.pt +3 -0
- checkpoint-1500/scheduler.bin +3 -0
- checkpoint-1600/optimizer.bin +3 -0
- checkpoint-1600/pytorch_model.bin +3 -0
- checkpoint-1600/random_states_0.pkl +3 -0
- checkpoint-1600/scaler.pt +3 -0
- checkpoint-1600/scheduler.bin +3 -0
- checkpoint-1700/optimizer.bin +3 -0
- checkpoint-1700/pytorch_model.bin +3 -0
- checkpoint-1700/random_states_0.pkl +3 -0
- checkpoint-1700/scaler.pt +3 -0
- checkpoint-1700/scheduler.bin +3 -0
- checkpoint-1800/optimizer.bin +3 -0
- checkpoint-1800/pytorch_model.bin +3 -0
- checkpoint-1800/random_states_0.pkl +3 -0
- checkpoint-1800/scaler.pt +3 -0
README.md
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---
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license: creativeml-openrail-m
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base_model: runwayml/stable-diffusion-v1-5
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tags:
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- stable-diffusion
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- stable-diffusion-diffusers
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- text-to-image
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- diffusers
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- lora
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inference: true
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---
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# LoRA text2image fine-tuning - hongrui/mammogram_v_2
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These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were fine-tuned on the hongrui/mammogram_v_1 dataset. You can find some example images in the following.
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checkpoint-1700/scaler.pt
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checkpoint-1700/scheduler.bin
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checkpoint-1800/optimizer.bin
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checkpoint-1800/pytorch_model.bin
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checkpoint-1800/random_states_0.pkl
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checkpoint-1800/scaler.pt
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|
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