Instructions to use RamAnanth1/sd-1-5-ram with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use RamAnanth1/sd-1-5-ram with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("RamAnanth1/sd-1-5-ram", 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 RamAnanth1/sd-1-5-ram: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/RamAnanth1/sd-1-5-ram/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://RamAnanth1/sd-1-5-ram/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/RamAnanth1/sd-1-5-ram/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 5275acefc9f7fe17848990c94356f4e6fe1ed0cec577432c45721ebdff7db0d3
- Size of remote file:
- 492 MB
- SHA256:
- b016ba8de19f519e9ae7e348388466d94759d040b357d0190d890846adcac7bc
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