How do I install the Lora Video Hosting skill?

Run npx skillmds@latest add pooriaarab/lora-video-hosting in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Lora Video Hosting safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Lora Video Hosting?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Lora Video Hosting free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Lora Video Hosting?

pooriaarab (@pooriaarab) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Lora Video Hosting by pooriaarab — Agent Skill

Name: Lora Video Hosting
Author: pooriaarab

Lora Video Hosting

Use when training a video LoRA and serving the results from a Cloudflare Workers app — picking a base model and GPU, curating a clip dataset, wiring Civitai and a rented-GPU endpoint, concatenating shots into a scene, and extracting a poster frame. Covers the local-dev traps that make a Workers video feed return an empty list.

pooriaarab 1dbb1c6 3.2 KB Updated Sep 17, 2026

File contents

LoRA Video Training & Hosting — Skill

Generic pattern for synthetic video LoRAs. No explicit content. Use for wellness / character video.

1. Training

Base: Wan 2.2-T2V-A14B — MoE, ~27B total params (14B active). Full bf16 weights alone exceed 24GB, so a single RTX 4090 only works for LoRA training if you quantize the frozen base to fp8 and/or use block-swap/CPU offload; without that, use a 48GB+ card (A6000/L40S). Use spot $0.30/hr Vast or Ubicloud managed.
LoRA type: DreamBooth-style video LoRA. Civitai types=LORA&baseModels=Wan Video 14B t2v, sort=Most Downloaded.
Dataset: 15–30 short clips (3–5s each), captioned. Curate via Civitai collections API (/api/v1/collections/{id}) or manual picks. Top LoRAs: Detail enhancer, FusionX, 360 rotation — all generic.
Train call: vast clone Wan + accelerate launch train_lora.py --base Wan-AI/Wan2.2-T2V-A14B --lora_rank 32 --learning_rate 1e-4
Checkpoint: Save as lora-{category}-{id}.safetensors to R2 loras/.

2. Hosting

GPU: RTX 4090D 24GB ($0.11 spot) or 4090 $0.30 flat. Ubicloud alternative: managed K8s with same image vastai/pytorch:2.6.0-cuda12.1-py310.
Endpoint: Put the rented box behind TLS (Cloudflare Tunnel or a Caddy reverse proxy) and call https://<tunnel-host>/v1/video — the raw http://<vast-ip>:8000 port sends prompts and generated video unencrypted across the public internet. Local fallback HF_TOKEN via https://router.huggingface.co/hf-inference.
Secrets: Keep in .dev.vars (wrangler reads it) + mirror to a local secrets file outside the repo. Keys: HF_TOKEN, CIVITAI_API_KEY, VAST_API_KEY, UBICLOUD_API_KEY. Never commit.
Cache: Civitai LoRAs cached 5m via Workers Cache API or KV (/tmp has no durable filesystem across Worker isolates). KV FLAGS for feature gates, D1 videos table for status.

3. Scene → Poster

Scene: Episode length is the sum of shot durations — chain 6–8 shots (8–10s each) to land near 60s, concatenated via ffmpeg. Prompt: cinematic, character, soft lighting, 720x1280 vertical.
Poster: Extract first frame at 1.2s via ffmpeg -ss 1.2 -i scene.mp4 -vframes 1 -s 720x1280 poster.jpg. Store posterUrl in D1 episodes.posterUrl, videoUrl points to R2 videos/{series}/{episode}.mp4.
Checkpoints: CP1 schema, CP2 poster pipeline, CP3 UI grid/modal.

4. Common Pitfalls

.open-next/worker.js 2.2K stub — run opennextjs-cloudflare build from the Next.js app directory, then move .open-next to the Worker root before wrangler dev --local --port 8788.
next dev has no D1/R2 bindings — use wrangler dev for feed, or detach via start_new_session to keep 8788 alive.
CIVITAI_API_KEY missing from the app's .dev.vars → empty LoRA list, with no error. Copy it from the repo root.

---name: lora-video-hostingdescription: Use when training a video LoRA and serving the results from a Cloudflare Workers app — picking a base model and GPU, curating a clip dataset, wiring Civitai and a rented-GPU endpoint, concatenating shots into a scene, and extracting a poster frame. Covers the local-dev traps that make a Workers video feed return an empty list.---# LoRA Video Training & Hosting — Skill> Generic pattern for synthetic video LoRAs. No explicit content. Use for wellness / character video.## 1. Training- **Base:** Wan 2.2-T2V-A14B — MoE, ~27B total params (14B active). Full bf16 weights alone exceed 24GB, so a single RTX 4090 only works for LoRA training if you quantize the frozen base to fp8 and/or use block-swap/CPU offload; without that, use a 48GB+ card (A6000/L40S). Use spot $0.30/hr Vast or Ubicloud managed.- **LoRA type:** DreamBooth-style video LoRA. Civitai `types=LORA&baseModels=Wan Video 14B t2v`, `sort=Most Downloaded`.- **Dataset:** 15–30 short clips (3–5s each), captioned. Curate via Civitai collections API (`/api/v1/collections/{id}`) or manual picks. Top LoRAs: Detail enhancer, FusionX, 360 rotation — all generic.- **Train call:** `vast clone Wan` + `accelerate launch train_lora.py --base Wan-AI/Wan2.2-T2V-A14B --lora_rank 32 --learning_rate 1e-4`- **Checkpoint:** Save as `lora-{category}-{id}.safetensors` to R2 `loras/`.## 2. Hosting- **GPU:** RTX 4090D 24GB ($0.11 spot) or 4090 $0.30 flat. Ubicloud alternative: managed K8s with same image `vastai/pytorch:2.6.0-cuda12.1-py310`.- **Endpoint:** Put the rented box behind TLS (Cloudflare Tunnel or a Caddy reverse proxy) and call `https://<tunnel-host>/v1/video` — the raw `http://<vast-ip>:8000` port sends prompts and generated video unencrypted across the public internet. Local fallback `HF_TOKEN` via `https://router.huggingface.co/hf-inference`.- **Secrets:** Keep in `.dev.vars` (wrangler reads it) + mirror to a local secrets file outside the repo. Keys: `HF_TOKEN`, `CIVITAI_API_KEY`, `VAST_API_KEY`, `UBICLOUD_API_KEY`. Never commit.- **Cache:** Civitai LoRAs cached 5m via Workers Cache API or KV (`/tmp` has no durable filesystem across Worker isolates). KV `FLAGS` for feature gates, D1 `videos` table for status.## 3. Scene → Poster- **Scene:** Episode length is the sum of shot durations — chain 6–8 shots (8–10s each) to land near 60s, concatenated via ffmpeg. Prompt: `cinematic, character, soft lighting, 720x1280 vertical`.- **Poster:** Extract first frame at 1.2s via `ffmpeg -ss 1.2 -i scene.mp4 -vframes 1 -s 720x1280 poster.jpg`. Store `posterUrl` in D1 `episodes.posterUrl`, `videoUrl` points to R2 `videos/{series}/{episode}.mp4`.- **Checkpoints:** CP1 schema, CP2 poster pipeline, CP3 UI grid/modal.## 4. Common Pitfalls- `.open-next/worker.js` 2.2K stub — run `opennextjs-cloudflare build` from the Next.js app directory, then move `.open-next` to the Worker root before `wrangler dev --local --port 8788`.- `next dev` has no D1/R2 bindings — use `wrangler dev` for feed, or detach via `start_new_session` to keep 8788 alive.- `CIVITAI_API_KEY` missing from the app's `.dev.vars` → empty LoRA list, with no error. Copy it from the repo root.

Frequently asked questions