MLX
mlx-lm
flowcast
loudink
loudink-v1.1
voice-agent
apple-silicon
compact-ir
dictation
computer-use
skills
record-and-replay
Instructions to use nsalerni/loudink-v1.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use nsalerni/loudink-v1.1 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir loudink-v1.1 nsalerni/loudink-v1.1
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
| license: apache-2.0 | |
| tags: | |
| - flowcast | |
| - loudink | |
| - loudink-v1.1 | |
| - voice-agent | |
| - mlx | |
| - apple-silicon | |
| - compact-ir | |
| - dictation | |
| - computer-use | |
| - skills | |
| - record-and-replay | |
| library_name: mlx-lm | |
| # loudink-v1.1 v1.1.0 (canary) | |
| On-device dual-stack for **LoudInk / Flowcast** on Apple Silicon, plus **user skills**: | |
| 1. **Writer** β LFM2.5-1.2B LoRA (dictation polish / messages / email / prompts) | |
| 2. **Planner** β FunctionGemma compact-IR LoRA (`run_skill` + freeform computer-use) | |
| 3. **Skill store** β local JSON skills (record β compile β voice replay) | |
| **Stable GA line:** [`nsalerni/loudink-v1`](https://huggingface.co/nsalerni/loudink-v1) (0.4.0 freeze). | |
| This package is the **v1.1 canary** (PR-AβE). Prefer dual-package client routing with kill-switch to v1. | |
| ## Product bars (v1.1) | |
| | Slice | Shipped | Neural | Latency | | |
| |-------|---------|--------|---------| | |
| | Writing daily | **100%** | **92.0%** | p50 **171 ms** | | |
| | Computer daily | **100%** | β | mostly fast-path | | |
| | Multi-step | **100%** | β | mostly fast-path | | |
| | **Daily-Mac overall (n=69)** | **100%** | β | β | | |
| | Skill invoke (n=19) | **100%** | β | deterministic store | | |
| | IR honesty (n=112, no FP) | β | **46.4%** | honesty lineage | | |
| Holds loudink-v1 0.4 bars; writing neural improved on expanded suite (~92% vs ~86%). | |
| ## Bundle layout | |
| ``` | |
| writer/ # optional promoted_core_100.safetensors seed adapter | |
| writer_unified/ # production writer LoRA | |
| ir/ # skill-aware IR LoRA | |
| ir_honesty_fallback/ # v0.4 honesty IR (optional rollback) | |
| skill_store/ # example seed skills (not user data) | |
| router.json | |
| manifest.json | |
| inference_config.json | |
| ``` | |
| **Bases are not vendored** (size). Pull 4-bit bases: | |
| - Writer: `mlx-community/LFM2.5-1.2B-Instruct-4bit` | |
| - IR: `mlx-community/functiongemma-270m-it-4bit` | |
| ## Skills (record β replay) | |
| ```python | |
| from huggingface_hub import snapshot_download | |
| from gemmaflow_tune.skills.store import SkillStore | |
| from gemmaflow_tune.skills.invoke import try_skill_invoke_plan | |
| bundle = snapshot_download("nsalerni/loudink-v1.1") | |
| store = SkillStore(f"{bundle}/skill_store") | |
| plan = try_skill_invoke_plan("run my invoice chase for Acme", skill_store=store) | |
| ``` | |
| Client should point `skill_store_path` at a **user-writable** directory and merge or replace example seeds. Private recordings stay local; do not train cloud models on them by default. | |
| ### IR extension | |
| ```json | |
| {"intent": "run_skill", "skill_id": "invoice_chase", "slots": {"company": "Acme"}, "confidence": 0.92} | |
| ``` | |
| Unknown `skill_id` β null plan (never invent). Freeform (`open gmail`) never hijacks skills. | |
| ### Vision (PR-E) | |
| `skills/vision.py` scaffold is in the training repo; default **disabled**. Client injects a resolver when ready. | |
| ## Integration | |
| ```python | |
| # runner_kind: loudink_v1 | |
| # skill_store_path: {bundle}/skill_store # or user path | |
| # ir_adapter_path: {bundle}/ir | |
| # writer_unified_adapter_path: {bundle}/writer_unified | |
| ``` | |
| See `inference_config.json` and `client_contract.md`. | |
| ## Methods (v1.1) | |
| - PR-A: Skill schema, store, recorder compiler, null-safe `run_skill` | |
| - PR-B: Paraphrase invoke + skill_invoke bench + light IR SFT | |
| - PR-C: Deterministic slot fill (`for` / `about` / named) | |
| - PR-D: Expanded daily-Mac computer + writing cases | |
| - PR-E: Vision fallback scaffold (noop until client wires resolver) | |
| ## License | |
| Apache-2.0 (adapters + example skills). Base model licenses apply to community 4-bit bases. **User-recorded skills are user data.** | |