Instructions to use deepgoyal19/new_lora1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use deepgoyal19/new_lora1 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("deepgoyal19/new_lora1") 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
Download checkpoint-60/optimizer.bin from deepgoyal19/new_lora1: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/deepgoyal19/new_lora1/resolve/main/checkpoint-60/optimizer.bin
- Command line
-
hf download hf://deepgoyal19/new_lora1/checkpoint-60/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/deepgoyal19/new_lora1/resolve/main/checkpoint-60/optimizer.bin
6.59 MB
- Xet hash:
- ea03019e340a67e127a4c5581b5d9cea77e96024fe30bdf51762f67fb55ba0f3
- Size of remote file:
- 6.59 MB
- SHA256:
- 1c0bd776cb484a80043e4ae2f5773ed9cd308cad06fb5d82de7618a168b8a327
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