zybrai-ml / README.md
zybrAI's picture
Upload 4 files
064b842 verified
|
Raw
History Blame Contribute Delete
1.55 kB
metadata
title: zybrAI ML Inference
emoji: 🛡️
colorFrom: purple
colorTo: indigo
sdk: docker
app_port: 7860
pinned: false

zybrAI ML Inference Space

Free CPU host for zybrAI's two ML classifiers (DeBERTa prompt-injection + toxic-RoBERTa), exposing them in the HF Inference API request/response shape so the zybrAI backend can call this Space directly.

Deploy (one-time, ~10 min)

  1. Go to https://huggingface.co/new-space
  2. Name it e.g. zybrai-ml, Space SDK = Docker, Hardware = CPU basic (free), visibility = Public (or Private + secret below).
  3. Upload the three files from this folder: app.py, requirements.txt, Dockerfile (and this README).
  4. The Space builds automatically. When it shows Running, note its URL: https://<your-username>-zybrai-ml.hf.space
  5. Test it: open https://<your-username>-zybrai-ml.hf.space/ — it should return {"status":"ok", ...}.

Point zybrAI at it

On the zybrAI backend (Render env vars, and locally for testing):

ML_MODE     = api
HF_API_BASE = https://<your-username>-zybrai-ml.hf.space
HF_API_KEY  = zybrai            # any value; must match SPACE_SECRET if you set one

Optional protection: set a Space Secret SPACE_SECRET=<something> and use the same value as HF_API_KEY on the backend, so only zybrAI can use your Space.

Note

Free CPU Spaces sleep after inactivity and cold-start on the next request (~10–30s for the first call, fast after). Fine for a demo; upgrade to a paid Space (always-on) later if you need consistent low latency.