Instructions to use plasmo/food-crit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use plasmo/food-crit with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("plasmo/food-crit", dtype=torch.bfloat16, device_map="cuda") prompt = "food_crit " image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder/pytorch_model.bin from plasmo/food-crit: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/plasmo/food-crit/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://plasmo/food-crit/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/plasmo/food-crit/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 67fb559b19029f5c48c207a96dc4a602965ff0c31b203835b77d3e72abaac375
- Size of remote file:
- 492 MB
- SHA256:
- aae31ccbde0363fb420c9521dc6eeb0b3086ab6bf76db06184444d7443894249
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