Instructions to use Muapi/take-a-taxi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/take-a-taxi with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Lightricks/LTX-Video", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muapi/take-a-taxi") prompt = "A man with short gray hair plays a red electric guitar." output = pipe(prompt=prompt).frames[0] export_to_video(output, "output.mp4") - LTX.io
How to use Muapi/take-a-taxi with LTX.io:
# Install the LTX-2 pipelines git clone https://github.com/Lightricks/LTX-2.git cd LTX-2 uv sync --frozen
# Download the weights from this repo, plus the Gemma text encoder hf download Muapi/take-a-taxi --local-dir models/take-a-taxi hf download google/gemma-3-12b-it-qat-q4_0-unquantized --local-dir models/gemma-3-12b
# Text/image-to-video with the LoRA on the HQ two-stage base pipeline uv run python -m ltx_pipelines.ti2vid_two_stages_hq \ --checkpoint-path path/to/checkpoint.safetensors \ --distilled-lora path/to/distilled_lora.safetensors 0.8 \ --spatial-upsampler-path path/to/spatial_upsampler.safetensors \ --gemma-root models/gemma-3-12b \ --lora models/take-a-taxi/<weights>.safetensors 1.0 \ --prompt "your prompt here" \ --output-path output.mp4 # For image-to-video, add: --image path/to/image.jpg 0 0.8 - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
| license: openrail++ | |
| library_name: diffusers | |
| base_model: Lightricks/LTX-Video | |
| tags: | |
| - lora | |
| - text-to-video | |
| - ltx | |
| - ltx-video | |
| - ltxv2 | |
| pipeline_tag: text-to-video | |
| # Take a taxi | |
|  | |
| **Base model**: LTXV2 | |
| **Trained words**: | |
| ## 🧠 Usage (Python) | |
| 🔑 **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys) | |
| ```python | |
| import requests, os | |
| url = "https://api.muapi.ai/api/v1/ltx_lora_video" | |
| headers = {"Content-Type": "application/json", "x-api-key": os.getenv("MUAPIAPP_API_KEY")} | |
| payload = { | |
| "prompt": "masterpiece, best quality", | |
| "lora_model": "take-a-taxi", | |
| "lora_strength": 1.0, | |
| "width": 768, | |
| "height": 512, | |
| "num_frames": 97 | |
| } | |
| print(requests.post(url, headers=headers, json=payload).json()) | |
| ``` | |