Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
dreambooth
diffusers-training
stable-diffusion
stable-diffusion-diffusers
Instructions to use Exc3ss/akshay_model_final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Exc3ss/akshay_model_final with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Exc3ss/akshay_model_final", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of Akshay Kumar" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-500/optimizer.bin from Exc3ss/akshay_model_final: direct link, hf CLI and curl.
- Browser
- Download file 1.73 GB
-
https://huggingface.co/Exc3ss/akshay_model_final/resolve/main/checkpoint-500/optimizer.bin
- Command line
-
hf download hf://Exc3ss/akshay_model_final/checkpoint-500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/Exc3ss/akshay_model_final/resolve/main/checkpoint-500/optimizer.bin
1.73 GB
- Xet hash:
- c53bde7ff7297ab198222d83e8b2fc005c42813d8c1539883f8d616258753917
- Size of remote file:
- 1.73 GB
- SHA256:
- 6935c6b31393b727ca6f4137b775d5af5b6366a50fb5bc509cf923984daa35a4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.