Lora Routing Private Models
fal · fal
Generative media inference — fal
Evaluates fal's Lora Routing Private Models across 8 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Generative media inference eval coverage.
About fal
fal is a generative media inference platform offering fast, scalable image, video, and audio generation through a simple API. It hosts leading open models (FLUX, Stable Diffusion, Whisper) and supports fine-tuned LoRA routing, webhooks, and queue-based async generation at production scale.
Sample tests· showing 3 of 8
| # | Input | Expected behavior | Check |
|---|---|---|---|
| 01 | Same user rapid edits on private app. | submit(..., hint='user-42'); reuse hint across session. | Pass / FailWorkflowmedium |
| 02 | Enterprise fine-tune isolated. | Use private endpoint string; separate API key scope [REQUIRES-VERIFICATION]. | Pass / FailWorkflowhigh |
| 03 | Custom video LoRA from short clips. | fal deploy training app; use returned endpoint in prod config; version revision pinned. | Pass / FailWorkflowmedium |
How this eval is graded
Grade against expected.ideal_behavior and expected.rubric.
Rubric criteria
- Fal
- Ai Platform
- Lora Routing Private Models
Recommended for
Works with
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ViewFrequently asked questions
What does the Lora Routing Private Models eval for fal fal test?+
Evaluates fal's Lora Routing Private Models across 8 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Generative media inference eval coverage.
How is the Lora Routing Private Models eval scored?+
The judge rubric: Grade against expected.ideal_behavior and expected.rubric.
How many test cases does this eval pack include?+
The Lora Routing Private Models pack for fal fal contains 8 test cases. 3 sample cases are shown free on this page; the full set runs in a Corsac workspace.
How do I run this eval?+
Sign up for Corsac, connect your model or agent endpoint, and run the Lora Routing Private Models pack as-is or after customizing thresholds. Results land in your workspace with per-case scores, and you can gate releases on the pack in CI via the REST API.
Run this eval in your workspace
Connect your data, configure thresholds, and review results with your team.