Text-to-Image
Diffusers
Safetensors
PyTorch
StableDiffusionPipeline
stable-diffusion
latent-diffusion
medical-imaging
brain-mri
multiple-sclerosis
dataset-conditioning
Instructions to use benetraco/latent_finetuning_encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use benetraco/latent_finetuning_encoder with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("benetraco/latent_finetuning_encoder", dtype=torch.bfloat16, device_map="cuda") 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
Upload README.md with huggingface_hub
Browse files
README.md
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- Beta schedule: linear (β_start=0.0001, β_end=0.02)
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- Gradient Clipping: Max norm 1.0
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- Mixed Precision: Disabled
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- Hardware: Single NVIDIA A30 GPU
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## ✍️ Fine-Tuning Strategy
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- Beta schedule: linear (β_start=0.0001, β_end=0.02)
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- Gradient Clipping: Max norm 1.0
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- Mixed Precision: Disabled
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- Hardware: Single NVIDIA A30 GPU
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## ✍️ Fine-Tuning Strategy
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