Instructions to use busetolunay/sam2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use busetolunay/sam2 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("busetolunay/sam2") prompt = "s34m is happily eating a burger and fries at a diner. Diner is car and race themed." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
sam2
A Flux LoRA trained on a local computer with Fluxgym

- Prompt
- s34m is happily eating a burger and fries at a diner. Diner is car and race themed.

- Prompt
- s34m is having a picnic by himself at the lakeside. There are food on the picnic blanket and there is a basket next to him.
Trigger words
You should use s34m 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 busetolunay/sam2
Base model
black-forest-labs/FLUX.1-dev