Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use PricedAsh/tomato-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use PricedAsh/tomato-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("PricedAsh/tomato-model", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of a 00_21 tomato plant" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-2000/optimizer.bin from PricedAsh/tomato-model: direct link, hf CLI and curl.
- Browser
- Download file 9.65 GB
-
https://huggingface.co/PricedAsh/tomato-model/resolve/main/checkpoint-2000/optimizer.bin
- Command line
-
hf download hf://PricedAsh/tomato-model/checkpoint-2000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/PricedAsh/tomato-model/resolve/main/checkpoint-2000/optimizer.bin
9.65 GB
- Xet hash:
- cded500560c02a14a4612948604ed639acefaf5320fdf65af4ca96cfe7568833
- Size of remote file:
- 9.65 GB
- SHA256:
- a83904b222f4c2341dbab7740940992aa1216273f3ac615552bd85c095ce27f0
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