Text-to-Image
Diffusers
Safetensors
stable-diffusion
stable-diffusion-diffusers
diffusers-training
lora
Instructions to use ValentinPeron/pokemon-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ValentinPeron/pokemon-lora 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("ValentinPeron/pokemon-lora") 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-2500/optimizer.bin from ValentinPeron/pokemon-lora: direct link, hf CLI and curl.
- Browser
- Download file 3.4 MB
-
https://huggingface.co/ValentinPeron/pokemon-lora/resolve/main/checkpoint-2500/optimizer.bin
- Command line
-
hf download hf://ValentinPeron/pokemon-lora/checkpoint-2500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/ValentinPeron/pokemon-lora/resolve/main/checkpoint-2500/optimizer.bin
3.4 MB
- Xet hash:
- 964b67531c0f1f0468f0a89ca75e86f5327ba402c530551574f7d75225488b12
- Size of remote file:
- 3.4 MB
- SHA256:
- bec03a531ba1cc478954d62f71426214e651364baf3e082226f53c56287b192a
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