Instructions to use DevonIT/hyd7150mdl-deep with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DevonIT/hyd7150mdl-deep 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-deep") prompt = "A blue and black cordless HYUNDAI HDY-7150 (hyd7150mdl) one-handed, small chainsaw on a white background." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
hyd7150mdl_deep
A Flux LoRA trained on a local computer with Fluxgym

- Prompt
- A blue and black cordless HYUNDAI HDY-7150 (hyd7150mdl) one-handed, small chainsaw on a white background.

- Prompt
- A blue and black cordless HYUNDAI HDY-7150 (hyd7150mdl) one-handed, small chainsaw used by a man in a garage on a working bench cutting a wooden piece.
Trigger words
You should use hyd7150mdl to trigger the image generation.
Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, Forge, etc.
Weights for this model are available in Safetensors format.
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Model tree for DevonIT/hyd7150mdl-deep
Base model
black-forest-labs/FLUX.1-dev