Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
dreambooth
diffusers-training
stable-diffusion
stable-diffusion-diffusers
lora
Instructions to use moobastresh/path-to-save-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use moobastresh/path-to-save-model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("moobastresh/path-to-save-model") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-500/optimizer.bin from moobastresh/path-to-save-model: direct link, hf CLI and curl.
- Browser
- Download file 2 GB
-
https://huggingface.co/moobastresh/path-to-save-model/resolve/main/checkpoint-500/optimizer.bin
- Command line
-
hf download hf://moobastresh/path-to-save-model/checkpoint-500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/moobastresh/path-to-save-model/resolve/main/checkpoint-500/optimizer.bin
2 GB
- Xet hash:
- 233a80fce041607688440eadfa3de53be4b426647ebc171ab5223692f2c06d26
- Size of remote file:
- 2 GB
- SHA256:
- ebc5c7acd2d950b29b33ffec9d30ea78f78a0cca5dd69bc9a8d9553b907c51be
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