Instructions to use nice2mitya/huynya with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nice2mitya/huynya with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("undefined", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("nice2mitya/huynya") prompt = "Niva" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from nice2mitya/huynya: direct link, hf CLI and curl.
- Browser
- Download file 562 Bytes
-
https://huggingface.co/nice2mitya/huynya/resolve/main/README.md
- Command line
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hf download hf://nice2mitya/huynya/README.md
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curl -L -o README.md https://huggingface.co/nice2mitya/huynya/resolve/main/README.md
562 Bytes
metadata
tags:
- flux
- text-to-image
- lora
- diffusers
- fal
base_model: undefined
instance_prompt: Niva
license: other
huynya
Model description
Niva
Trigger words
You should use Niva to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Training at fal.ai
Training was done using fal.ai/models/fal-ai/hunyuan-video-lora-training.