--- license: other license_name: zyphra-zaya language: - en library_name: mlx tags: - applescript - macos - computer-use - agent - tool-calling - function-calling - mlx - moe - osaurus base_model: Zyphra/ZAYA1-8B pipeline_tag: text-generation --- ![Osaurus](./osaurus-x-banner.png) # Osaurus-AppleScript-8B-JANG_6M **A fast, small tool-calling model for macOS AppleScript & agentic computer-use.** Given a `run_applescript` tool, it emits a structured **tool call** with valid AppleScript to drive macOS — app automation (Safari, Finder, Mail, Notes, Calendar, System Events), system control, clipboard, screenshots, and `do shell script` — ready to execute in an agent loop. Without a tools spec, it writes AppleScript directly (hybrid). Built by **[Osaurus](https://osaurus.ai)**. Base: **Zyphra/ZAYA1-8B** (MoE). Quantized with **JANG** (6-bit affine, MLX-native) for fast on-device inference via [MLX](https://github.com/ml-explore/mlx). Verified in the Osaurus runtime. | | | |---|---| | Parameters | 8.84 B (MoE, 16 experts) | | Quant | **JANG 6-bit** — 6-bit affine weights + 8-bit embeddings (MLX `mx.quantize`, group 32) | | Size | ~7.4 GB | | Tool-calling | native (``), `run_applescript` | | Runtime | MLX (Apple Silicon) / Osaurus | ## Benchmark — base vs final (held-out executable AppleScript bench, 87 tasks) *Tool-call emission* = emits a `run_applescript` call. *Compile* = the emitted script is valid AppleScript. *Exec* = it runs and returns the correct result (scored on the pure-computational subset with a deterministic answer). | | Tool-call emission | Compile | Exec | |---|---|---|---| | Base (Zyphra/ZAYA1-8B) | ✗ (writes raw text, no tool calls) | 28.9% | 30.0% | | **Osaurus-AppleScript-8B-JANG_6M** | **100%** ⭐ | **80%** ⭐ | **75%** ⭐ | The fine-tune teaches structured tool-calling **and** valid AppleScript (base does neither). Typical app-automation tool-calls sit at the compile tier; the exec column is the hardest computational subset (string/number algorithms, shell, coercions). ## Usage (MLX, tool-calling) ```python from mlx_lm import load, generate model, tok = load("OsaurusAI/Osaurus-AppleScript-8B-JANG_6M") tools = [{"type":"function","function":{"name":"run_applescript", "description":"Execute AppleScript on macOS and return its output.", "parameters":{"type":"object","properties":{"script":{"type":"string"}},"required":["script"]}}}] msgs = [{"role":"user","content":"Get the URL of the front Safari tab."}] prompt = tok.apply_chat_template(msgs, tools=tools, add_generation_prompt=True, tokenize=False) print(generate(model, tok, prompt=prompt, max_tokens=300)) # -> ... ... ``` Your agent parses the `run_applescript` tool call, runs the script (e.g. via `osascript`), and feeds the result back. (Omit `tools=` to get raw AppleScript instead.) ## Tiers For higher accuracy use **`OsaurusAI/Osaurus-AppleScript-16B-A4B-JANG_4M`**. This 8B is the fast/small tier for low-latency on-device automation. ## License Inherits the **Zyphra/ZAYA1-8B** license — review and comply with the base model's terms. --- Made by Osaurus · contact **eric@osaurus.ai**