Ai avatar video skills inference sh ai avatar video
Skill bg-szy/TOP-SKILLS/skills/marketplace/ai-avatar-video__skills-inference-sh-ai-avatar-video
全球最大的 Claude Code 技能聚合库 · 收录 3900+ 来自 12+ 来源的技能,提供在线搜索与趋势分析看板 / The world's largest Claude Code skill aggregation hub — 3900+ skills from 12+ sources with online search and trend dashboard
npx -y skills add bg-szy/TOP-SKILLS --skill ai-avatar-video__skills-inference-sh-ai-avatar-videoAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
- 4 stars4 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
What its author says it does
Copied from the file, not written here
Create AI avatar and talking head videos with OmniHuman, Fabric, PixVerse via inference.sh CLI. Models: OmniHuman 1.5, OmniHuman 1.0, Fabric 1.0, PixVerse Lipsync. Capabilities: audio-driven avatars, lipsync videos, talking head generation, virtual presenters. Use for: AI presenters, explainer videos, virtual influencers, dubbing, marketing videos. Triggers: ai avatar, talking head, lipsync, avatar video, virtual presenter, ai spokesperson, audio driven video, heygen alternative, synthesia alternative, talking avatar, lip sync, video avatar, ai presenter, digital human
SKILL.md
4.3 KB, ~1.1k tokens by cl100k_base, as published. Nobody here has run it
AI Avatar & Talking Head Videos
Create AI avatars and talking head videos via inference.sh CLI.
Quick Start
curl -fsSL https://cli.inference.sh | sh && infsh login
# Create avatar video from image + audio
infsh app run bytedance/omnihuman-1-5 --input '{
"image_url": "https://portrait.jpg",
"audio_url": "https://speech.mp3"
}'
Available Models
| Model | App ID | Best For |
|---|---|---|
| OmniHuman 1.5 | bytedance/omnihuman-1-5 | Multi-character, best quality |
| OmniHuman 1.0 | bytedance/omnihuman-1-0 | Single character |
| Fabric 1.0 | falai/fabric-1-0 | Image talks with lipsync |
| PixVerse Lipsync | falai/pixverse-lipsync | Highly realistic |
Search Avatar Apps
infsh app list --search "omnihuman"
infsh app list --search "lipsync"
infsh app list --search "fabric"
Examples
OmniHuman 1.5 (Multi-Character)
infsh app run bytedance/omnihuman-1-5 --input '{
"image_url": "https://portrait.jpg",
"audio_url": "https://speech.mp3"
}'
Supports specifying which character to drive in multi-person images.
Fabric 1.0 (Image Talks)
infsh app run falai/fabric-1-0 --input '{
"image_url": "https://face.jpg",
"audio_url": "https://audio.mp3"
}'
PixVerse Lipsync
infsh app run falai/pixverse-lipsync --input '{
"image_url": "https://portrait.jpg",
"audio_url": "https://speech.mp3"
}'
Generates highly realistic lipsync from any audio.
Full Workflow: TTS + Avatar
# 1. Generate speech from text
infsh app run infsh/kokoro-tts --input '{
"text": "Welcome to our product demo. Today I will show you..."
}' > speech.json
# 2. Create avatar video with the speech
infsh app run bytedance/omnihuman-1-5 --input '{
"image_url": "https://presenter-photo.jpg",
"audio_url": "<audio-url-from-step-1>"
}'
Full Workflow: Dub Video in Another Language
# 1. Transcribe original video
infsh app run infsh/fast-whisper-large-v3 --input '{"audio_url": "https://video.mp4"}' > transcript.json
# 2. Translate text (manually or with an LLM)
# 3. Generate speech in new language
infsh app run infsh/kokoro-tts --input '{"text": "<translated-text>"}' > new_speech.json
# 4. Lipsync the original video with new audio
infsh app run infsh/latentsync-1-6 --input '{
"video_url": "https://original-video.mp4",
"audio_url": "<new-audio-url>"
}'
Use Cases
- Marketing: Product demos with AI presenter
- Education: Course videos, explainers
- Localization: Dub content in multiple languages
- Social Media: Consistent virtual influencer
- Corporate: Training videos, announcements
Tips
- Use high-quality portrait photos (front-facing, good lighting)
- Audio should be clear with minimal background noise
- OmniHuman 1.5 supports multiple people in one image
- LatentSync is best for syncing existing videos to new audio
Related Skills
# Full platform skill (all 150+ apps)
npx skills add inference-sh/skills@inference-sh
# Text-to-speech (generate audio for avatars)
npx skills add inference-sh/skills@text-to-speech
# Speech-to-text (transcribe for dubbing)
npx skills add inference-sh/skills@speech-to-text
# Video generation
npx skills add inference-sh/skills@ai-video-generation
# Image generation (create avatar images)
npx skills add inference-sh/skills@ai-image-generation
Browse all video apps: infsh app list --category video
Documentation
- Running Apps - How to run apps via CLI
- Content Pipeline Example - Building media workflows
- Streaming Results - Real-time progress updates
Gives 0 of the 12 instructions most video audio skills give in ~1.1k tokens
Counted across 621 of the 795 authors here whose files we hold, read 2026-08-06
- read individual rule files for detailed explanationsin 21 of 621, across 9 files
- Use WAV PCM 16kHz mono audio formatin 13 of 621, across 4 files
- render final videoin 13 of 621, across 6 files
- use this skill when dealing with Remotion codein 11 of 621, across 4 files
- save generated audio to a WAV filein 11 of 621, across 4 files
- handle conversion errors gracefullyin 10 of 621, across 6 files
- add captions to videos alwaysin 10 of 621, across 4 files
- generate music from text descriptions using MusicGenin 9 of 621, across 2 files
- do not skip pipeline layersin 9 of 621, across 3 files
- do not make one tool do everythingin 9 of 621, across 3 files
- never ask the user to paste their full API keyin 9 of 621, across 3 files
- use azure document intelligence for complex pdfsin 9 of 621, across 4 files
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.