Instructions to use Muapi/beeg-big-breasts-ltx2.3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/beeg-big-breasts-ltx2.3 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", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muapi/beeg-big-breasts-ltx2.3") prompt = "A man with short gray hair plays a red electric guitar." output = pipe(prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
Add Beeg (Big) Breasts - LTX2.3
Browse files- .gitattributes +1 -0
- README.md +38 -0
- beeg-big-breasts-ltx2.3.safetensors +3 -0
- preview.jpg +3 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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preview.jpg filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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license: openrail++
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library_name: diffusers
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base_model: Lightricks/LTX-Video
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tags:
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- lora
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- text-to-video
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- ltx
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- ltx-video
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- ltxv-2.3
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pipeline_tag: text-to-video
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---
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# Beeg (Big) Breasts - LTX2.3
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**Base model**: LTXV 2.3
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**Trained words**: BEEG
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## 🧠 Usage (Python)
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🔑 **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
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```python
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import requests, os
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url = "https://api.muapi.ai/api/v1/ltx_lora_video"
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headers = {"Content-Type": "application/json", "x-api-key": os.getenv("MUAPIAPP_API_KEY")}
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payload = {
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"prompt": "masterpiece, best quality",
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"lora_model": "beeg-big-breasts-ltx2.3",
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"lora_strength": 1.0,
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"width": 768,
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"height": 512,
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"num_frames": 97
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}
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print(requests.post(url, headers=headers, json=payload).json())
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```
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beeg-big-breasts-ltx2.3.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:ed4c430f52908c55691c68c34870d3f9e19f1cbde6950e3952f5d96bf3350c65
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size 528939336
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preview.jpg
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Git LFS Details
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