Instructions to use anupamtripathi/model_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use anupamtripathi/model_2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("anupamtripathi/model_2", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of a Oculus device" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-100/optimizer.bin from anupamtripathi/model_2: direct link, hf CLI and curl.
- Browser
- Download file 6.85 MB
-
https://huggingface.co/anupamtripathi/model_2/resolve/main/checkpoint-100/optimizer.bin
- Command line
-
hf download hf://anupamtripathi/model_2/checkpoint-100/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/anupamtripathi/model_2/resolve/main/checkpoint-100/optimizer.bin
6.85 MB
- Xet hash:
- ef9a70062693564aa9c9f0125021eff4b1551320b0a4234c234a6cca8153ace5
- Size of remote file:
- 6.85 MB
- SHA256:
- a8fb63c6b41ed00d5ef735a8a1700caa9f52df05160e0382d0ca7428a0c92748
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.