Instructions to use siraxe/H3_slider_experiments with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use siraxe/H3_slider_experiments 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("MiniMaxAI/MiniMax-H3", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("siraxe/H3_slider_experiments") prompt = "H3_CAMERA_ARC_slider (+ 2.0 4.0 6.0)" output = pipe(prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Inference
- Notebooks
- Google Colab
- Kaggle
File size: 731 Bytes
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language:
- en
tags:
- text-to-audio
- lora
- minimax-h3
- diffusers
- speed
- slider
- detail
pipeline_tag: text-to-video
base_model: MiniMaxAI/MiniMax-H3
pretty_name: h3 slider experiments
widget:
- output:
url: vid/w5.mp4
text: "H3_CAMERA_ARC_slider (+ 2.0 4.0 6.0)"
- output:
url: vid/w3.mp4
text: "H3_DETAIL_slider"
- output:
url: vid/w2.mp4
text: "H3_SPEED_slider"
- output:
url: vid/w4.mp4
text: "H3_SMEAR_slider , +12 vs -12"
- output:
url: vid/w1.mp4
text: "sun fog slider"
---
<Gallery />
H3 experimental slider tests
No specific prompt needed , describe effect as it and slider lora will make it pronounced
Provided as is , pruned rank4 versions might be cleaner at higher values |