Instructions to use codermert/malikafinal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use codermert/malikafinal 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("codermert/malikafinal") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
| 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 | |
| language: | |
| - en | |
| tags: | |
| - flux | |
| - diffusers | |
| - lora | |
| - stable-diffusion | |
| - text-to-image | |
| base_model: "black-forest-labs/FLUX.1-dev" | |
| pipeline_tag: text-to-image | |
| inference: true # Bu satırı ekleyin | |
| # Malika | |
| <Gallery /> | |
| ## Usage with 🧨 Diffusers | |
| ```python | |
| from diffusers import DiffusionPipeline | |
| import torch | |
| # Load base model | |
| pipeline = DiffusionPipeline.from_pretrained( | |
| "black-forest-labs/FLUX.1-dev", | |
| torch_dtype=torch.float16 | |
| ).to("cuda") | |
| # Load your LoRA | |
| pipeline.load_lora_weights( | |
| "codermert/malikafinal", | |
| weight_name="lora.safetensors", | |
| adapter_name="malika" | |
| ) | |
| # Generate image | |
| image = pipeline( | |
| prompt="portrait of TOK, <malika>, photorealistic, 8K", | |
| negative_prompt="blurry, deformed" | |
| ).images[0] |