Instructions to use DevonIT/hyd7150mdl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DevonIT/hyd7150mdl with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("DevonIT/hyd7150mdl") prompt = "A HYUNDAI HYD-7150 (hyd7150mdl) model." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download hyd7150mdl.safetensors from DevonIT/hyd7150mdl: direct link, hf CLI and curl.
- Browser
- Download file 39.8 MB
-
https://huggingface.co/DevonIT/hyd7150mdl/resolve/main/hyd7150mdl.safetensors
- Command line
-
hf download hf://DevonIT/hyd7150mdl/hyd7150mdl.safetensors
-
curl -L -o hyd7150mdl.safetensors https://huggingface.co/DevonIT/hyd7150mdl/resolve/main/hyd7150mdl.safetensors
39.8 MB
- Xet hash:
- b2612b529df891df21e2c5d3b355ee2a5f7acaa2e372d99bac6766d0ef05bea5
- Size of remote file:
- 39.8 MB
- SHA256:
- d80b5422cf688485afb86667c334c970bc222ff1e9bcd15c3b87fc2de8f87ba7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.