Add LFM2.5-230M tool-caller as Core AI ANE static .aimodel (int4 palettized, 512 ctx, coreai-torch 0.4.1)

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+ane-static/uncle_rudy_lfm2_230m_toolcaller_int4pal/uncle_rudy_lfm2_230m_toolcaller_int4pal.aimodel/main.mlirb filter=lfs diff=lfs merge=lfs -text

LICENSE

@@ -0,0 +1,71 @@
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README.md

@@ -0,0 +1,180 @@
+---
+license: other
+license_name: lfm1.0
+license_link: LICENSE
+base_model: LiquidAI/LFM2.5-230M
+tags:
+  - coreai
+  - aimodel
+  - apple-silicon
+  - on-device
+  - neural-engine
+  - lfm2
+  - hybrid
+  - tool-calling
+  - function-calling
+pipeline_tag: text-generation
+---
+
+# Uncle Rudy — LFM2.5-230M tool-caller — Apple Core AI (`.aimodel`)
+
+A **LoRA fine-tune of [LiquidAI/LFM2.5-230M](https://huggingface.co/LiquidAI/LFM2.5-230M)** that turns
+a single spoken/typed utterance into a **JSON tool call** for a to-do app — converted to Apple's
+**Core AI** `.aimodel` format and running on the **Neural Engine** (iOS 27 / macOS 27).
+
+> [!IMPORTANT]
+> This is a **static-shape / Neural Engine** bundle (4 entrypoints: `load_embeddings`,
+> `gather_embeddings`, `extend_*`, `prompt_opt_*`) → Apple's `EngineFactory` selects the
+> **`static-shape`** engine. It is **not** a `gpu-pipelined` decode bundle, so it will **not**
+> load on the `coreai-pipelined` GPU path that most published Core AI chat bundles use.
+> It also needs a small runtime patch — see [Runtime requirements](#runtime-requirements).
+
+## What it does
+
+Give it one utterance; it emits one tool call.
+
+```
+"Remind me to buy milk"                  → {"name":"create_todo","arguments":{"title":"Buy milk","due":null}}
+"Remind me to call the dentist tomorrow" → {"name":"create_todo","arguments":{"title":"Call the dentist","due":"tomorrow"}}
+"Delete the dentist task"                → {"name":"delete_todo","arguments":{"target":"Call the dentist"}}
+```
+
+Tool surface: `create_todo` (`title`, `due`) · `set_status` (`target`, `status`) ·
+`update_todo` (`target`, `title`, `due`) · `delete_todo` (`target`).
+
+Apply the bundle's own chat template and feed the raw utterance as the user turn — the fine-tune
+emits the assistant tool call directly. **No system prompt / tool-schema preamble is needed**
+(training used `mask_prompt`, so loss was computed only on the tool-call tokens). Decode **greedily**.
+
+## Bundle
+
+```
+ane-static/uncle_rudy_lfm2_230m_toolcaller_int4pal/
+├── uncle_rudy_lfm2_230m_toolcaller_int4pal.aimodel/   # main.mlirb · main.hash · metadata.json
+├── tokenizer/                                          # tokenizer.json · tokenizer_config.json
+│                                                       # chat_template.jinja · generation_config.json
+└── metadata.json                                       # LanguageBundle manifest
+```
+
+| | |
+|---|---|
+| Base | LiquidAI/LFM2.5-230M (14 layers = 8 short-conv + 6 GQA attention, hidden 1024, 16/8 heads, vocab 65536, tied embeddings) |
+| Fine-tune | LoRA r=16, scale 16, 400 iters, `mask_prompt: true` (loss on tool call only), fused |
+| Compression | `4bit_weight_palettized_group32` (embedding table int8, per Core AI's iOS path) |
+| Size | **144 MB** `.aimodel` (~148 MB with tokenizer) |
+| Max context | **512** (prompt + generation) — deliberately small; see [Context length](#context-length) |
+| Engine | `static-shape` (Neural Engine) |
+
+## Runtime requirements
+
+1. **iOS 27 / macOS 27** — Core AI ships with the OS. **Device-only on iOS**: `CoreAI.framework` is
+   in the iPhoneOS SDK but **not** the iOS Simulator SDK, so this cannot run in the Simulator.
+2. **Toolchain ≥ beta 3 era.** This bundle was exported with **`coreai-torch 0.4.1` / `coreai-core 1.0.0b2`**
+   so it carries the *versioned-IR* location format the beta-3 on-device compiler requires. (Bundles
+   exported with the June-era `coreai-torch 0.4.0` / `coreai-core 1.0.0b1` fail on beta 3 with
+   `expected AICode versioned location … Failed to convert to versioned IR … cannot unwrap empty odiec_module_t`.)
+3. **A conv-cache extra-state patch on the static-shape engine.** LFM2 is a conv+attention hybrid: its
+   short-conv layers carry a rolling **conv cache** *in addition to* the KV cache, so the model exports
+   **three** states (`key_cache`, `value_cache`, `conv_cache`). Apple's `StaticShapeEngine` hardcodes two.
+   The engine must allocate the extra state, **zero-fill it on reset** (unlike KV it is read directly, not
+   mask-gated), and bind it by name each step.
+
+> Note: the conv state cannot be partially prefix-rewound (it only holds the last `L-1` columns), so a
+> conv model should reprocess each request from scratch rather than reuse a partial KV prefix.
+
+## Use it
+
+The bundle is a standard `LanguageBundle` (`.aimodel` + `tokenizer/` + `metadata.json`) — point the
+runtime at the **bundle directory**:
+
+```swift
+import CoreAILanguageModels
+
+let bundle    = try LanguageBundle(at: bundleDir)          // dir containing the .aimodel
+let engine    = try await CoreAIRunner(from: bundle).makeInferenceEngine()  // → static-shape / ANE
+let tokenizer = try await bundle.loadTokenizer()
+
+let generator = try await TextGeneratorBuilder()
+    .withInferenceEngine(engine)
+    .withTokenizer(tokenizer)
+    .withSampling(configuration: .greedy)
+    .build()
+
+// `.prompt` applies the bundle's chat template; the fine-tune emits the tool call.
+let json = try await generator.generate(input: .prompt("Remind me to buy milk"), maxTokens: 60)
+```
+
+Catalog entry, for apps that pull Core AI bundles from HF by tree path:
+
+```swift
+ModelSpec(
+    bundleName:   "uncle_rudy_lfm2_230m_toolcaller_int4pal",
+    hfRemotePath: "ane-static/uncle_rudy_lfm2_230m_toolcaller_int4pal",
+    repoURL:      "https://huggingface.co/sabeshbesh/uncle-rudy-lfm2-230m-CoreAI",
+    label:        "Uncle Rudy 230M",
+    approxSizeGB: 0.15,
+    warmupToken:  1,
+    maxContext:   512)
+```
+
+⚠️ A catalog/`ModelSpec` alone is not sufficient: an app wired to the **`coreai-pipelined`** engine
+must route this bundle to the **static-shape** engine and carry the conv-cache patch above.
+
+## First load is slow — by design
+
+The **first** load on a given device compiles the model's Neural Engine graphs **on-device**, inside
+Apple's `AIModel(contentsOf:options:)`. This cannot be shipped precompiled — the compiled program is
+specific to that device + OS. The OS caches the result, so every later load is near-instant.
+
+| | |
+|---|---|
+| Cold (first) load, Apple Silicon ANE | **~54 s** |
+| Warm load (cached) | **~0.02–0.1 s** |
+
+### Context length
+
+Exported at **512** context on purpose. The iOS static export fans out one specialized ANE graph per
+`(context_bucket × query_length)` per function — at 2048 that is **24** graphs and a **~151 s** cold
+compile; at 512 it is **12** graphs and **~54 s**. A tool-caller only ever sees a short utterance plus
+a ≤60-token call, so 512 is ample. Re-export at a larger `--max-context-length` if you need more, and
+pay the longer one-time compile.
+
+## Measured
+
+Greedy, `llm-runner`, **macOS / Apple Silicon Neural Engine** (this bundle):
+
+| | |
+|---|---|
+| Prefill | ~80–330 tok/s |
+| Decode | ~73–83 tok/s |
+
+> iPhone on-device throughput is **not yet published** — these are Mac-ANE numbers for the same bundle.
+> Treat them as indicative, not as iPhone figures.
+
+**Correctness.** The re-authored BC1S / Neural-Engine model was gated against the fp32 Hugging Face
+reference: **100% next-token top-1 match (12/12 positions)**, logits PSNR ~52 dB, on a truncated model
+covering both layer types (conv + attention). The lower-than-macOS PSNR (~70 dB on the GPU/dynamic
+path) is expected: the iOS path int8-quantizes the embedding table and computes attention per-head,
+which reassociates fp16 arithmetic — every argmax still matches.
+
+## Conversion notes
+
+Converted from the fused Hugging Face checkpoint via a custom Core AI recipe on top of
+[apple/coreai-models](https://github.com/apple/coreai-models). Two things were needed beyond the
+stock pipeline:
+
+- **MLX → PyTorch conv-weight transpose.** `mlx_lm fuse` writes depthwise Conv1d weights in MLX axis
+  order `(out, kernel, in)` = `[1024, 3, 1]`; PyTorch's `modeling_lfm2` wants `(out, in, kernel)` =
+  `[1024, 1, 3]`. Only the 8 conv layers are affected (Linear/embedding/norm layouts are identical),
+  and the fix is an axis swap — verified bit-exact against the base weights.
+- **Re-authoring for the Neural Engine.** BC1S `(B, C, 1, S)` layout, projections as 1×1 `Conv2d`,
+  per-head attention (no fused SDPA on ANE), transposed causal mask using `-40000` rather than `-inf`,
+  and the short conv as a depthwise `Conv2d(D, D, (1, L), groups=D)` over the sequence axis, with the
+  conv cache threaded as a third functional state.
+
+## License
+
+Weights derive from [LiquidAI/LFM2.5-230M](https://huggingface.co/LiquidAI/LFM2.5-230M) and are
+redistributed under the **LFM Open License v1.0** ([LICENSE](LICENSE)) — Apache-style grants, but
+**commercial use is licensed only for entities under US$10M annual revenue** (qualified non-profits
+exempt for non-commercial/research use). Review the LICENSE before any commercial deployment.

ane-static/uncle_rudy_lfm2_230m_toolcaller_int4pal/metadata.json

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+{
+  "metadata_version": "0.2",
+  "kind": "llm",
+  "name": "uncle_rudy_lfm2_230m_toolcaller_int4pal",
+  "assets": {
+    "main": "uncle_rudy_lfm2_230m_toolcaller_int4pal.aimodel"
+  },
+  "language": {
+    "tokenizer": "LiquidAI/LFM2.5-230M",
+    "vocab_size": 65536,
+    "max_context_length": 512,
+    "embedded_tokenizer": true,
+    "function_map": {
+      "main": [
+        "main"
+      ]
+    }
+  },
+  "source": {
+    "model_definition": "torch",
+    "hf_model_id": "LiquidAI/LFM2.5-230M"
+  },
+  "compression": "4bit_weight_palettized_group32",
+  "compilation": {
+    "date": "2026-07-13T19:16:31.555725+05:30",
+    "targets": []
+  }
+}

ane-static/uncle_rudy_lfm2_230m_toolcaller_int4pal/tokenizer/chat_template.jinja

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+{{- bos_token -}}
+{%- set preserve_thinking = preserve_thinking | default(false) -%}
+
+{%- macro format_arg_value(arg_value) -%}
+    {%- if arg_value is string -%}
+        {{- "'" + arg_value + "'" -}}
+    {%- elif arg_value is mapping -%}
+        {{- arg_value | tojson -}}
+    {%- else -%}
+        {{- arg_value | string -}}
+    {%- endif -%}
+{%- endmacro -%}
+
+{%- macro parse_content(content) -%}
+    {%- if content is string -%}
+        {{- content -}}
+    {%- else -%}
+        {%- set _ns = namespace(result="") -%}
+        {%- for item in content -%}
+            {%- if item["type"] == "image" -%}
+                {%- set _ns.result = _ns.result + "<image>" -%}
+            {%- elif item["type"] == "text" -%}
+                {%- set _ns.result = _ns.result + item["text"] -%}
+            {%- else -%}
+                {%- set _ns.result = _ns.result + item | tojson -%}
+            {%- endif -%}
+        {%- endfor -%}
+        {{- _ns.result -}}
+    {%- endif -%}
+{%- endmacro -%}
+
+{%- macro render_tool_calls(tool_calls) -%}
+    {%- set tool_calls_ns = namespace(tool_calls=[]) -%}
+    {%- for tool_call in tool_calls -%}
+        {%- set func_name = tool_call["function"]["name"] -%}
+        {%- set func_args = tool_call["function"]["arguments"] -%}
+        {%- set args_ns = namespace(arg_strings=[]) -%}
+        {%- for arg_name, arg_value in func_args.items() -%}
+            {%- set args_ns.arg_strings = args_ns.arg_strings + [arg_name + "=" + format_arg_value(arg_value)] -%}
+        {%- endfor -%}
+        {%- set tool_calls_ns.tool_calls = tool_calls_ns.tool_calls + [func_name + "(" + (args_ns.arg_strings | join(", ")) + ")"] -%}
+    {%- endfor -%}
+    {{- "<|tool_call_start|>[" + (tool_calls_ns.tool_calls | join(", ")) + "]<|tool_call_end|>" -}}
+{%- endmacro -%}
+
+{%- set ns = namespace(system_prompt="", last_user_index=-1) -%}
+{%- if messages[0]["role"] == "system" -%}
+    {%- if messages[0].get("content") -%}
+        {%- set ns.system_prompt = parse_content(messages[0]["content"]) -%}
+    {%- endif -%}
+    {%- set messages = messages[1:] -%}
+{%- endif -%}
+{%- if tools -%}
+    {%- set ns.system_prompt = ns.system_prompt + ("\n" if ns.system_prompt else "") + "List of tools: [" -%}
+    {%- for tool in tools -%}
+        {%- if tool is not string -%}
+            {%- set tool = tool | tojson -%}
+        {%- endif -%}
+        {%- set ns.system_prompt = ns.system_prompt + tool -%}
+        {%- if not loop.last -%}
+            {%- set ns.system_prompt = ns.system_prompt + ", " -%}
+        {%- endif -%}
+    {%- endfor -%}
+    {%- set ns.system_prompt = ns.system_prompt + "]" -%}
+{%- endif -%}
+{%- if ns.system_prompt -%}
+    {{- "<|im_start|>system\n" + ns.system_prompt + "<|im_end|>\n" -}}
+{%- endif -%}
+{%- for message in messages -%}
+    {%- if message["role"] == "user" -%}
+        {%- set ns.last_user_index = loop.index0 -%}
+    {%- endif -%}
+{%- endfor -%}
+{%- for message in messages -%}
+    {{- "<|im_start|>" + message.role + "\n" -}}
+    {%- if message.role == "assistant" -%}
+        {%- generation -%}
+        {%- if message.thinking is defined and (preserve_thinking or loop.index0 > ns.last_user_index) -%}
+            {{- "<think>" + message.thinking + "</think>" -}}
+        {%- endif -%}
+        {%- set _cfm_tag = "CONTINUE_FINAL_MESSAGE_TAG " -%}
+        {%- set _has_cfm = false -%}
+        {%- if message.content is defined -%}
+            {%- set content = parse_content(message.content) -%}
+            {%- if not (preserve_thinking or loop.index0 > ns.last_user_index) -%}
+                {%- if "</think>" in content -%}
+                    {%- set content = content.split("</think>")[-1] | trim -%}
+                {%- endif -%}
+            {%- endif -%}
+            {%- if message.tool_calls is defined and content.endswith(_cfm_tag) -%}
+                {%- set _has_cfm = true -%}
+                {%- set _trunc_len = (content | length) - (_cfm_tag | length) -%}
+                {{- content[:_trunc_len] -}}
+            {%- else -%}
+                {{- content -}}
+            {%- endif -%}
+        {%- endif -%}
+        {%- if message.tool_calls is defined -%}
+            {{- render_tool_calls(message.tool_calls) -}}
+        {%- endif -%}
+        {%- if _has_cfm -%}
+            {{- _cfm_tag -}}
+        {%- endif -%}
+        {{- "<|im_end|>\n" -}}
+        {%- endgeneration -%}
+    {%- else %}
+        {%- if message.get("content") -%}
+            {{- parse_content(message["content"]) -}}
+        {%- endif -%}
+        {{- "<|im_end|>\n" -}}
+    {%- endif %}
+{%- endfor -%}
+{%- if add_generation_prompt -%}
+    {{- "<|im_start|>assistant\n" -}}
+{%- endif -%}

ane-static/uncle_rudy_lfm2_230m_toolcaller_int4pal/tokenizer/generation_config.json

@@ -0,0 +1,14 @@
+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 7,
+  "output_attentions": false,
+  "output_hidden_states": false,
+  "pad_token_id": 0,
+  "do_sample": true,
+  "temperature": 0.1,
+  "top_k": 50,
+  "repetition_penalty": 1.05,
+  "transformers_version": "5.2.0",
+  "use_cache": true
+}

ane-static/uncle_rudy_lfm2_230m_toolcaller_int4pal/tokenizer/tokenizer_config.json

@@ -0,0 +1,19 @@
+{
+  "backend": "tokenizers",
+  "bos_token": "<|startoftext|>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "is_local": true,
+  "legacy": false,
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<|pad|>",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "TokenizersBackend",
+  "use_default_system_prompt": false,
+  "use_fast": true
+}

ane-static/uncle_rudy_lfm2_230m_toolcaller_int4pal/uncle_rudy_lfm2_230m_toolcaller_int4pal.aimodel/main.hash

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+�#�*<'����������]�&Xr�1��3#

ane-static/uncle_rudy_lfm2_230m_toolcaller_int4pal/uncle_rudy_lfm2_230m_toolcaller_int4pal.aimodel/main.mlirb

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+version https://git-lfs.github.com/spec/v1
+oid sha256:912308a32a3c1727f4ababf8ff830bbcb8ab915da50e265872f18c31fbb13323
+size 150825615

ane-static/uncle_rudy_lfm2_230m_toolcaller_int4pal/uncle_rudy_lfm2_230m_toolcaller_int4pal.aimodel/metadata.json

@@ -0,0 +1,5 @@
+{
+  "producer" : "coreai-core 1.0.0b2",
+  "assetVersion" : "2.0",
+  "creationDate" : "20260713T134631Z"
+}

config.json

@@ -0,0 +1,7 @@
+{
+  "model_type": "coreai-aimodel",
+  "format": "aimodel",
+  "framework": "Apple Core AI (iOS 27 / macOS 27)",
+  "engine": "static-shape (Neural Engine)",
+  "note": "Fine-tuned LFM2.5-230M tool-caller converted to an Apple Core AI .aimodel. This is a STATIC-SHAPE / Neural Engine bundle (4 entrypoints), not a gpu-pipelined decode bundle. See README.md for the bundle layout, the required runtime patch, and run instructions."
+}