Instructions to use Cossale/frames with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Cossale/frames 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", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Cossale/frames") prompt = "a road leading to a mountain in a night, visible moon and stars. FRM$" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 1,114 Bytes
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tags:
- text-to-image
- flux
- lora
- diffusers
- template:sd-lora
- fluxgym
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: FRM$
license: other
license_name: flux-1-dev-non-commercial-license
license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
widget:
- text: a road leading to a mountain in a night, visible moon and stars. FRM$
output:
url: images/example_du3zlevlr.png
- text: >-
a snowy mountain with lavander haze over the horizon, distant mountain,
evening time, birds. FRM$
output:
url: images/example_ajesrotih.png
- text: >-
a mountain range with a large mountain in center, dusk, no sun, forest,
pink dominated image. FRM$
output:
url: images/example_m0sl2j6rp.png
---
# Frames
A Flux LoRA trained on a local computer with [Fluxgym](https://github.com/cocktailpeanut/fluxgym)
<Gallery />
## Trigger words
You should use `FRM$` 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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