Instructions to use jinofcoolnes/corporate_memphis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jinofcoolnes/corporate_memphis with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jinofcoolnes/corporate_memphis", dtype=torch.bfloat16, device_map="cuda") 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 text_encoder/pytorch_model.bin from jinofcoolnes/corporate_memphis: direct link, hf CLI and curl.
- Browser
- Download file 134 Bytes
-
https://huggingface.co/jinofcoolnes/corporate_memphis/resolve/d86a1db1561dba234644250b34c5428f80dcd1ce/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://jinofcoolnes/corporate_memphis@d86a1db1561dba234644250b34c5428f80dcd1ce/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jinofcoolnes/corporate_memphis/resolve/d86a1db1561dba234644250b34c5428f80dcd1ce/text_encoder/pytorch_model.bin
134 Bytes
- Xet hash:
- 90bb0b452770dc6172999be0fc42883b630c177b65c25f329192ddb81db57d01
- Size of remote file:
- 134 Bytes
- SHA256:
- 62d4b554b61a007eb429dde4940c71162bfae81f7568db4a0fdbfc2addd333be
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