Instructions to use Jemmo/ProtonX50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jemmo/ProtonX50 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("Jemmo/ProtonX50") prompt = "A sleek, red x50style car drifts around a corner on a racetrack, leaving a trail of smoke behind it. The car's low, aerodynamic design is emphasized as it takes the turn at high speed, with its tires gripping the asphalt. The night background shows a racetrack with safety barriers and a distant cityscape under a night cloudy sky, which is lit by the setting moon, casting a warm glow over the scene. The motion blur and smoke create a dynamic sense of speed and intensity, capturing the thrill of high-performance racing. reflection." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Upload ProtonX50.safetensors
Browse files- ProtonX50.safetensors +3 -0
ProtonX50.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:2171a2fbd650d401fd76392144d1300a4907e3c3f805af55dbdc277ed9523c8d
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size 171969344
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