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| title: README | |
| emoji: 🐼 | |
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| license: apache-2.0 | |
| <img src="hero.png" alt="ZeroShotLab" width="100%" /> | |
| <br/> | |
| <p><strong>EDGE AI RESEARCH LAB · INDIA</strong></p> | |
| # ZeroShotLab | |
| **On-device AI agents for phones** — local computer, efficient micro-models, privacy by default. | |
| We build the stack where the model, tools, and memory stay on the device. First product ship is **L2 Hinglish micro-models**; the parallel track is a **phone-native agent harness** (file/shell sandbox + E2E messaging later). We do **not** start with a giant model zoo. | |
| Website: [zeroshotlab.in](https://zeroshotlab.in) · GitHub: [zeroshotlab-ai](https://github.com/zeroshotlab-ai) | |
| --- | |
| ## Mission | |
| Make capable AI agents practical on real ₹8–15k Androids: low latency, offline-friendly, and under the user’s control — not locked behind cloud APIs. | |
| --- | |
| ## Product stack | |
| | Track | What | Target ship | Status | | |
| | --- | --- | --- | --- | | |
| | **L2 — Micro-models** | Hinglish **LID · transliteration · normaliser · PII** (20–100M, ONNX int8) — also harness pre/post tools | **Now → Jan 2027** | **START HERE** | | |
| | **Agent runtime** | On-device harness + local file/shell (“own computer”) + OTS GGUF/LiteRT bases | Phase 0 Nov 2026 → Kotlin MVP Jan–Feb 2027 | Parallel with L2 | | |
| | **L3 — Instruct** | Hinglish instruct 1–4B (LoRA/QLoRA ± DPO), quantised — only if L2 eval proves the gap | **Feb 2027** (or when needed) | After L2 | | |
| | **L4 — TTS** | Hindi/Hinglish on-device TTS | Mar 2027 (conditional) | **Cut first if late** | | |
| | **L5 — SDK** | Edge SDK + Android sample (agent + L2 tools ± L3) | **Apr 2027** | Alpha | | |
| | **L1 — Zoo** | Indic edge model zoo + device benchmarks | Optional later | **Deferred** — not a gate | | |
| --- | |
| ## Public roadmap (Nov 2026 → Apr 2027) | |
| ### Now → mid-Jan 2027 — **L2 alpha** | |
| - Freeze scope: 4 micros × ONNX int8 | |
| - Datasets + licences + **rule baselines** to beat | |
| - ONNX int8 export + phone RTF measurements on budget Androids | |
| - Train/distill micros; kill any run that does not beat rule baseline | |
| - **Ship gate:** ≥2 of 4 models on this Hub + short write-up + Android/ONNX sample | |
| ### Parallel — **Agent Phase 0 → MVP** | |
| - Study harness patterns (AndroidHarness / AndroPI / Mochu — study only, no clone) | |
| - Termux + off-the-shelf GGUF smoke on a real phone | |
| - Native Kotlin harness MVP (**Jan–Feb 2027**) feeding L5 | |
| ### Feb 2027 — **L3** (if needed) | |
| - Tool-aware Hinglish instruct on OTS Gemma/Qwen-class bases | |
| - Must beat base on held-out eval and run on a budget phone | |
| ### Mar 2027 — **L4** (conditional) | |
| - Only with consented data + native-listener MOS | |
| - If late: **drop / slip** — do not block L2/L3/L5 | |
| ### Apr 2027 — **L5 SDK + agent sample** | |
| - Python + Android sample: L2 tools + OTS runtime ± L3 | |
| - Public **HinglishEdge-Eval**-style table | |
| --- | |
| ## L2 detail — what ships first | |
| | Micro-model | Job | | |
| | --- | --- | | |
| | **LID** | Language / script / Hinglish-mix detect | | |
| | **Transliteration** | Roman ↔ Devanagari (scoped) | | |
| | **Normaliser** | Clean noisy Hinglish for downstream | | |
| | **PII** | Redact/flag phone, email, etc. before tools/logs | | |
| **Hard rules:** no train-from-scratch · no L1 zoo as a blocker · every release needs a public eval · prefer Apache/MIT bases · Modal free / Kaggle first (budget alert at $30). | |
| --- | |
| ## Week-by-week (L2 critical path) | |
| | When | Milestone | | |
| | --- | --- | | |
| | 6–12 Nov 2026 | Scope freeze · orgs · LICENSES · Modal alert | | |
| | 6–14 Nov | Dataset + licence shortlist · rule baselines | | |
| | 9–20 Nov | ONNX int8 pipeline · phone RTF script | | |
| | 16–29 Nov | First 2 micros trained vs baseline | | |
| | 16 Nov–20 Dec | Eval set v0 (reviewed Hinglish) | | |
| | 30 Nov–20 Dec | Remaining micros · HF packages · harness hooks | | |
| | **by mid-Jan 2027** | **L2 alpha publish** (≥2/4) | | |
| --- | |
| ## Why investors / partners should care | |
| 1. **Clear wedge:** phone-native agents + India-first Hinglish tooling — not another hosted chatbot. | |
| 2. **Lean path:** L2 GPU budget on the order of tens of dollars; phones ₹20–40k test fleet; revenue from **paid edge pilots**, not a race-to-bottom API. | |
| 3. **Honest gates:** ship only what beats baselines; L4 and L1 zoo are explicitly cuttable. | |
| 4. **Apr 2027 north star:** public models + agent sample + eval table + pilot/LOI conversations from results. | |
| --- | |
| ## Links | |
| - Website: [zeroshotlab.in](https://zeroshotlab.in) | |
| - GitHub org: [github.com/zeroshotlab-ai](https://github.com/zeroshotlab-ai) | |
| - Hub org: [huggingface.co/zeroshotlab](https://huggingface.co/zeroshotlab) | |
| --- | |
| *India · Edge AI · Building in public · Plan as of 6 Nov 2026 IST · dates are targets, not promises* | |