LFM3-1.7B on Core AI: the Mac bundle (gpu-pipelined/lfm3_1_7b_decode_int8hu_block32_sym_pf64, int8 with main + a 64-token prefill) and the iPhone 18 Pro bundle (ios-h19p, the static Neural Engine form compiled for h19p), card, LICENSE, SHA256SUMS

.gitattributes

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README.md

@@ -0,0 +1,200 @@
+---
+library_name: coreai
+license: other
+license_name: lfm1.0
+license_link: https://huggingface.co/mlboydaisuke/LFM3-1.7B-CoreAI/blob/main/LICENSE
+base_model: LiquidAI/LFM3-1.7B
+tags:
+  - coreai
+  - aimodel
+  - apple-silicon
+  - on-device
+  - lfm3
+  - hybrid
+  - reasoning
+  - tool-calling
+pipeline_tag: text-generation
+base_model_relation: quantized
+---
+
+# LFM3-1.7B — Apple Core AI (`.aimodel`)
+
+LiquidAI's [LFM3-1.7B](https://huggingface.co/LiquidAI/LFM3-1.7B) converted to Apple's Core AI (iOS 27 /
+macOS 27): a 1.7B model that reasons before it answers and calls tools in XML, in two bundles with a 4,096-token
+context. The Mac bundle is one int8 `.aimodel` on the `coreai-pipelined` GPU engine that prefills a prompt 64
+tokens at a time; the iPhone 18 Pro bundle is a Neural Engine build with fixed input shapes, compiled in advance for
+that phone's chip (`h19p`).
+[CoreAIKit](https://github.com/john-rocky/coreai-kit)'s `ChatSession` and Apple's `LanguageModelSession` drove
+both in the checks below; CoreAIKit's LFM3 support is not in a release or on the kit's main branch
+([Use it](#use-it)).
+
+Source: [`LiquidAI/LFM3-1.7B`](https://huggingface.co/LiquidAI/LFM3-1.7B) at revision
+`ac2586a34f1a1c03329dbdcdefabd8b6478ddaa7`. Conversion code, gates and notes:
+[coreai-model-zoo](https://github.com/john-rocky/coreai-model-zoo/tree/main/models/lfm3-1.7b).
+
+## Bundles
+
+| path | size | for | what is in it |
+|---|---:|---|---|
+| `gpu-pipelined/lfm3_1_7b_decode_int8hu_block32_sym_pf64/` | 2.72 GB | Mac | `lfm3_1_7b_decode_int8hu_block32_sym_pf64.aimodel`, `metadata.json`, `tokenizer/` (the source's tokenizer files; the chat template is the vendor's with eight rewrites that render the same string under transformers and parse in swift-jinja 2.3.2 and 2.3.6) |
+| `ios-h19p/` | 2.16 GB | iPhone 18 Pro | `lfm3_1_7b_static_pal8_tanh_block_c4096.h19p.ane.aimodelc` (compiled for the iPhone 18 Pro's Neural Engine, `h19p`; its `resources.bin` holds 1.48 GB of weights), `metadata.json`, `tokenizer/` (the same four files) |
+
+**Mac.** `int8hu`: the MLP and conv-mixer linears int8 per-block-32, the head untied and int8 per-block-32
+symmetric, the attention projections (q, k, v, o and the gate) and the q / k norms in fp32, everything else fp16.
+The `.aimodel` holds two functions over the same weights: `main` takes one token per step and `prefill` takes 64;
+the pipelined engine sends the prompt through `prefill` 64 tokens at a time while more than 64 tokens remain, and
+the last 1–64 tokens through `main` one at a time. On a Mac, Core AI compiles the `.aimodel` for the GPU the first
+time it loads and caches the result.
+
+**iPhone 18 Pro.** The same 24 layers rebuilt the way Apple's iOS Neural Engine path requires (fixed shapes
+throughout), with each conv layer's input history kept in its own rows of the KV cache, the sliding window made from
+the engine's causal mask, 8-bit palettized weights (k-means, groups of 32; the attention gate fp16) and the tied
+head as an int8 table.
+It holds contexts of 256 to 4,096 tokens with queries of 8, 16 or 64 tokens, and the compile puts each of its 30
+transformer functions in a Neural Engine region. It is compiled for `h19p` only: no other iPhone has a bundle here.
+
+## Speed
+
+**Mac** (M4 Max, macOS 27.0), from a 1,024-token prompt: prefill 1,234 tok/s, 0.83 s to the first token, decode
+169.5 tok/s (median of 8 runs, 2026-10-31; the published `.aimodel`, compiled on first load, run by the
+coreai-models version CoreAIKit pins: the path an app that uses CoreAIKit takes; `llm-benchmark` with 256 generated
+tokens, one process per run). Compiled ahead of time for the Mac GPU it is slower: decode 105.5 tok/s and 1.00 s to
+the first token in the same window.
+
+In that window, alternated with it on the same 1,024 prompt tokens, MLX (mlx-vlm 0.7.11) decodes LiquidAI's
+8-bit weights at 189.8 tok/s and llama.cpp (b12001) their Q8_0 at 180.2, both faster than this bundle, and their
+4-bit forms faster still (286.9 and 242.1); their bf16 and F16 forms are slower (113.1 and 111.1). All six reach
+the first token in 0.23–0.26 s, and every form, this one included, gives transformers bf16's verdicts on the 8
+questions below. What this port adds is a Neural Engine bundle for the iPhone and tool calls through Apple's
+`LanguageModelSession`.
+
+**iPhone 18 Pro** (iOS 27.2), a 768-token prompt and 256 generated tokens: prefill 590.6 tok/s, decode 47.17
+tok/s (medians of 6 trials), one turn 6.71 s (768 / prefill + 255 / decode, not timed), peak footprint 2.82 GB,
+thermal state nominal at the start and end of every run. In the gate app the first load on the phone took 34.9 s
+and later loads 4.4 s or less; CoreAIKit's test app, with the bundle at its own path, took 32.4 s on its first
+load, then 3.7 s and 0.4 s.
+
+## What was checked
+
+Against transformers 5.20.2 on the same weights.
+
+The Mac bundle, on a Mac (M4 Max, macOS 27.0):
+
+- **Teacher-forced on 17 sequences** (8 questions with thinking off and on, a 1,648-token document) against
+  transformers fp32, with the `.aimodel` compiled ahead of time for the Mac GPU and the prompts fed the way the
+  engine feeds them (64-token chunks through `prefill`, the rest one token at a time): top-1
+  **2639 / 2682 = 98.40 %** (2,683 positions; the one where transformers' own top-2 gap is under 1e-3 is not
+  counted); one token at a time throughout: 2637 / 2682. At every chunk boundary the logits agree with the
+  one-token path to cos ≥ 0.99999.
+- **8 questions, thinking off**, greedy: 8 / 8, the same verdicts as transformers bf16.
+- **Token gate** (16 greedy tokens vs the fp32 oracle): 16 / 16, also on a 215-token prompt that rides three
+  chunks; a chat turn stops on `<|im_end|>`.
+- **Thinking on**, the same 8 questions, greedy, 3,584-token budget, 3 runs of fresh processes: every run 8 / 8 —
+  `</think>` closes after 40–237 tokens (median 56) and the answer after it is right (run on the `main`-only
+  build of the same weights: prompts this short never reach `prefill`, and `main` gives the same values).
+- **A tool call**, a tool returning a fresh random value, 3 runs each through CoreAIKit's `KitLanguageModel` and the
+  zoo's `ZooLanguageModel`: 6 / 6 with the value in the answer verbatim.
+- **The bytes published here**: the `.aimodel` is the export re-saved without its source locations (a new
+  `main.hash`); run again, its teacher-forced values equal the export's at all 2,683 positions, fed in chunks and
+  one token at a time, and the 8 questions, the token gate and the stop-token check give the same results.
+- **The kit's path** (the `.aimodel` specialized on load, as timed above; the teacher-forced pass above was not
+  repeated on this path): the 8 questions 8 / 8 with the same
+  replies as the ahead-of-time build, the token gate 16 / 16 on both prompts, and the stop-token turn stops after 6
+  tokens (`1+1=2`; transformers fp32 stops after 2, at a step where its own top-2 gap is 0.005). Through
+  CoreAIKit (`ChatSession` and `KitLanguageModel`), the 8 questions with thinking on (3 launches) and off, a tool
+  round trip and a 3-turn chat pass.
+
+The iPhone bundle, on an iPhone 18 Pro (iPhone19,2, iOS 27.2), through the fixed-shape (`static-shape`) engine of the
+coreai-models version CoreAIKit pins:
+
+- **Teacher-forced** over the replies of the same 17 sequences (721 steps, up to 64 a sequence after its prompt)
+  against transformers fp32: top-1 **692 / 721 = 95.98 %** (bar 93 %; every step's fp32 top-2 gap is at least
+  1e-3). The tokens equal those of Apple's own static engine on an iPhone 17 Pro on all 18 prompts, teacher-forced
+  and generated, and a poisoned fixture fails, as it must.
+- **8 questions, thinking off**: 8 / 8, the verdicts of transformers bf16; the stop-token turn stops after 6 tokens.
+- **CoreAIKit's catalog path**: `ChatSession(catalog: "lfm3-1.7b")` takes the `ios` variant and loads `ios-h19p/`
+  (copied into the kit's model store at the path a download would use, so no download ran) on the static-shape
+  engine. Thinking on, the 8
+  questions in 3 fresh launches: 8 / 8 each, `</think>` inside the budget and the reasoning out of the answer.
+  Thinking off: 8 / 8. A tool round trip through `KitLanguageModel` and `LanguageModelSession`: 3 / 3 with the
+  value verbatim. With the default configuration, "What is 17 + 25? Answer briefly." gets "17 + 25 = 42.", and a
+  3-turn chat recalls its first turn, every turn ending on the stop token.
+- With thinking off, 1 of the 8 questions ("How do you say 'thank you' in French?") still opens `<think>` and
+  reasons for 68 tokens before its answer, which gives "Merci"; transformers bf16 and the Mac bundle answer it
+  directly. Apple's engine on the iPhone 17 Pro does the same, so this comes from the Neural Engine export itself,
+  not from CoreAIKit's engine.
+
+The full table, the transcripts and how the fp16 activations set a floor on this model are on the
+[zoo card](https://github.com/john-rocky/coreai-model-zoo/tree/main/models/lfm3-1.7b) and in
+[the port notes](https://github.com/john-rocky/coreai-model-zoo/blob/main/knowledge/lfm3-1.7b-port.md).
+
+## Use it
+
+CoreAIKit's support for LFM3 — the XML tool calls, the reasoning stream, the thinking switch and the
+`lfm3-1.7b` catalog entry — is not in a CoreAIKit release or on the kit's main branch (0.7.3 does not support
+LFM3). The CoreAIKit checks above ran a kit build that has it; with such a build, on a Mac or an iPhone 18 Pro:
+
+```swift
+import CoreAIKit
+
+let chat = try await ChatSession(catalog: "lfm3-1.7b")
+for try await event in await chat.streamResponse(to: "What is 17 + 25? Answer briefly.") {
+    switch event {
+    case .thinking(let delta): print(delta, terminator: "")   // the reasoning comes first
+    case .response(let delta): print(delta, terminator: "")   // then the answer
+    default: break
+    }
+}
+```
+
+Thinking is on by default (the chat template ends the prompt with `<think>`); `maxResponseTokens` covers the
+reasoning and the answer together. `ChatSession.Configuration.enableThinking = false` renders the template's
+thinking-off prompt; LiquidAI notes that turning thinking off "can be inconsistent, especially for
+reasoning-heavy tasks".
+
+Tool calls come out as XML (`<tool_call>` / `<function=NAME>` / `<parameter=KEY>`). CoreAIKit's `KitLanguageModel`
+renders the tools the way the chat template does and parses these calls for Apple's `LanguageModelSession` — the
+tool-call checks above.
+
+On an iPhone the kit takes `ios-<arch>/` for the architecture Core AI reports for the phone
+(`AIModel.deviceArchitectureName`: `h19p` on the iPhone 18 Pro) and falls back to `ios/`. This repo has
+`ios-h19p/` only, so on any other iPhone (the iPhone 17 Pro, which reports `h18p`, included) the kit finds no
+bundle and throws `variantNotFound` before it downloads anything. Both apps that ran the iPhone checks carried the
+`com.apple.developer.kernel.increased-memory-limit` entitlement (peak footprint 2.82 GB in the gate app, up to 2.94 GB
+through `ChatSession`); a run without it was not tried.
+
+Without the kit: the Mac gates ran `llm-runner` built from the zoo's fork of
+[apple/coreai-models](https://github.com/apple/coreai-models), whose pipelined engine carries the conv state as an
+extra state and finds the `prefill` function by name, with `COREAI_CHUNK_THRESHOLD=1` and
+`--inference-engine-variant coreai-pipelined --warmup off`; the iPhone checks ran the `StaticShapeEngine` of that
+fork's tag `0.2.8-zoo`, the one CoreAIKit pins.
+
+## Limits
+
+- The Mac bundle cannot resume a conversation from its middle: the engine cannot rewind its conv state, so a new
+  conversation starts from zero state, and CoreAIKit's `ChatSession` prefills the whole
+  history again each turn (a three-turn chat recalled its first turn). The iPhone bundle keeps the conv history in
+  the KV cache, and in the 3-turn chat its engine reused the earlier turns' prompt tokens (32, then 70).
+- On the Mac the engine always runs the last prompt token through the one-token `main` function, so a prompt's
+  final 1–64 tokens run one at a time at about the decode speed: a 1,024-token prompt runs 15 chunks and then 64
+  single steps.
+- 4,096-token context in both bundles.
+- The iPhone bundle is for the iPhone 18 Pro only; the iPhone 17 Pro has no bundle here. The Mac bundle is not for
+  iPhones: on an iPhone 18 Pro the `main`-only `.aimodel`, specializing on the phone (device JIT), had not built its
+  engine 300 s after launch (the cause is not isolated), and on an iPhone 17 Pro the same int8 weights compiled
+  ahead of time for its GPU decoded at 9.25 tok/s (median of 4 trials at thermal state serious; 10.5 in the first
+  run, at fair), that compile holding fp16 copies of the int8 linears.
+- On a Mac, Core AI named an ahead-of-time compile's
+  cache entry after its graph and not its weights, so a second compile of the same graph with other weights ran
+  with the first one's weights (not checked on an iPhone): an app that switches between such compiles should
+  delete that compile-cache entry first. The Mac bundle is a JIT `.aimodel`, whose cache entry name covers its
+  weights.
+
+## License
+
+The weights are under the **LFM Open License v1.0**
+([LICENSE](https://huggingface.co/mlboydaisuke/LFM3-1.7B-CoreAI/blob/main/LICENSE), carried from
+[`LiquidAI/LFM3-1.7B`](https://huggingface.co/LiquidAI/LFM3-1.7B)): Apache-2.0-style grants, with §5:
+commercial use by a legal entity at or above US$10 M annual revenue is not licensed (the threshold does not
+apply to a qualified non-profit's non-commercial or research use). Converted from LiquidAI's weights; not
+affiliated with Apple or LiquidAI.

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+bf028f813efc6137bc07ed045cafe71820df9a5e26a38e39954706ed1e30a457  ios-h19p/tokenizer/tokenizer_config.json
+4d28ca14dedc0b3d0fcc2b3339f0e79931faa33874f3d24f522183a8fc70068c  LICENSE
+3cb5759dbe5f540da374735804ea4bea62ddd9c5866512b1546ea98f84ac0004  README.md

config.json

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+{
+  "architectures": [
+    "Lfm3ForCausalLM"
+  ],
+  "auto_map": {
+    "AutoConfig": "configuration_lfm3.Lfm3Config",
+    "AutoModel": "modeling_lfm3.Lfm3Model",
+    "AutoModelForCausalLM": "modeling_lfm3.Lfm3ForCausalLM"
+  },
+  "bos_token_id": 124894,
+  "conv_L_cache": 7,
+  "conv_bias": false,
+  "dtype": "bfloat16",
+  "eos_token_id": 124900,
+  "head_dim": 128,
+  "hidden_size": 2048,
+  "intermediate_size": 7680,
+  "layer_types": [
+    "conv",
+    "conv",
+    "full_attention",
+    "conv",
+    "sliding_attention",
+    "conv",
+    "full_attention",
+    "conv",
+    "sliding_attention",
+    "conv",
+    "full_attention",
+    "conv",
+    "sliding_attention",
+    "conv",
+    "full_attention",
+    "conv",
+    "sliding_attention",
+    "conv",
+    "full_attention",
+    "conv",
+    "sliding_attention",
+    "conv",
+    "full_attention",
+    "conv"
+  ],
+  "max_position_embeddings": 262144,
+  "model_type": "lfm3",
+  "norm_eps": 1e-05,
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "num_key_value_heads": 4,
+  "pad_token_id": 124893,
+  "rope_parameters": {
+    "full_attention": {
+      "partial_rotary_factor": 0.5,
+      "rope_theta": 1000000.0,
+      "rope_type": "default"
+    },
+    "sliding_attention": {
+      "rope_theta": 10000,
+      "rope_type": "default"
+    }
+  },
+  "sliding_window": 256,
+  "tie_word_embeddings": true,
+  "transformers_version": "5.12.1",
+  "use_cache": true,
+  "use_sandwich_norm": true,
+  "vocab_size": 128000
+}

gpu-pipelined/lfm3_1_7b_decode_int8hu_block32_sym_pf64/lfm3_1_7b_decode_int8hu_block32_sym_pf64.aimodel/main.hash

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gpu-pipelined/lfm3_1_7b_decode_int8hu_block32_sym_pf64/lfm3_1_7b_decode_int8hu_block32_sym_pf64.aimodel/main.mlirb

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5d4b6a8986bb81efc9ae5a66e7d53ca7d7e8b89d1d5e23188f6f89ec06fec171
+size 2701679977

gpu-pipelined/lfm3_1_7b_decode_int8hu_block32_sym_pf64/lfm3_1_7b_decode_int8hu_block32_sym_pf64.aimodel/metadata.json

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+{
+  "creationDate" : "20261029T185953Z",
+  "assetVersion" : "2.0",
+  "producer" : "coreai-core 1.0.0b2"
+}

gpu-pipelined/lfm3_1_7b_decode_int8hu_block32_sym_pf64/metadata.json

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+{
+  "metadata_version": "0.2",
+  "kind": "llm",
+  "name": "lfm3_1_7b_decode_int8hu_block32_sym_pf64",
+  "assets": {
+    "main": "lfm3_1_7b_decode_int8hu_block32_sym_pf64.aimodel"
+  },
+  "language": {
+    "tokenizer": "LiquidAI/LFM3-1.7B",
+    "vocab_size": 128000,
+    "max_context_length": 4096,
+    "embedded_tokenizer": true,
+    "function_map": {
+      "main": [
+        "main",
+        "prefill"
+      ]
+    },
+    "chat_template_sha256": "48f23f8579dda4c39f48ff0a9c5f22e68e6b3267898dc9316e9b4161e56643be"
+  },
+  "source": {
+    "model_definition": "torch",
+    "hf_model_id": "LiquidAI/LFM3-1.7B",
+    "hf_revision": "ac2586a34f1a1c03329dbdcdefabd8b6478ddaa7"
+  },
+  "compression": {
+    "scheme": "int8hu"
+  },
+  "lfm3": {
+    "inputs": [
+      "input_ids",
+      "position_ids"
+    ],
+    "outputs": [
+      "logits"
+    ],
+    "states": [
+      "keyCache",
+      "valueCache",
+      "convState"
+    ],
+    "kv_slots": [
+      2,
+      4,
+      6,
+      8,
+      10,
+      12,
+      14,
+      16,
+      18,
+      20,
+      22
+    ],
+    "conv_slots": [
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+      1,
+      3,
+      5,
+      7,
+      9,
+      11,
+      13,
+      15,
+      17,
+      19,
+      21,
+      23
+    ],
+    "sliding_window": 256,
+    "prefill_chunk": 64
+  },
+  "compilation": {
+    "date": "2026-10-29T18:59:59.507395+00:00",
+    "targets": []
+  },
+  "strip": {
+    "what": "the .aimodel re-saved after coreai-torch's strip_debug_info: every op's source location (file path, call stack) replaced by an unknown location; the ops and the weights are not touched",
+    "from_main_mlirb": {
+      "bytes": 2701984448,
+      "sha256": "a3a59a7a44b5a573bea4f01928de6be4ff5f539a56f3fbacb50bc2ea5494a961"
+    },
+    "main_mlirb": {
+      "bytes": 2701679977,
+      "sha256": "5d4b6a8986bb81efc9ae5a66e7d53ca7d7e8b89d1d5e23188f6f89ec06fec171"
+    },
+    "tool": "coreai_torch.debugging.debug_info.strip_debug_info",
+    "versions": {
+      "coreai-torch": "0.4.1",
+      "coreai-core": "1.0.0b2"
+    }
+  }
+}

gpu-pipelined/lfm3_1_7b_decode_int8hu_block32_sym_pf64/tokenizer/chat_template.jinja

@@ -0,0 +1,308 @@
+{{- bos_token -}}
+{%- set preserve_thinking = preserve_thinking | default(false) -%}
+{%- set enable_thinking = enable_thinking | default(true) -%}
+
+{%- macro _json(v) -%}
+    {%- if ([1, 2] | tojson) == "[1, 2]" -%}
+        {{- v | tojson -}}
+    {%- elif v is string -%}
+        {{- '"' + (v | replace('\\', '\\\\') | replace('"', '\\"') | replace('\n', '\\n') | replace('\r', '\\r') | replace('\t', '\\t') | replace('\b', '\\b') | replace('\f', '\\f')) + '"' -}}
+    {%- elif v is boolean -%}
+        {{- "true" if v else "false" -}}
+    {%- elif v is none -%}
+        {{- "null" -}}
+    {%- elif v is mapping -%}
+        {%- set _jn = namespace(out="{", first=true) -%}
+        {%- for _jk, _jv in v.items() -%}
+            {%- set _jn.out = _jn.out + ("" if _jn.first else ", ") + _json(_jk | string) + ": " + _json(_jv) -%}
+            {%- set _jn.first = false -%}
+        {%- endfor -%}
+        {{- _jn.out + "}" -}}
+    {%- elif v is sequence -%}
+        {%- set _jn = namespace(out="[", first=true) -%}
+        {%- for _jx in v -%}
+            {%- set _jn.out = _jn.out + ("" if _jn.first else ", ") + _json(_jx) -%}
+            {%- set _jn.first = false -%}
+        {%- endfor -%}
+        {{- _jn.out + "]" -}}
+    {%- else -%}
+        {{- v | string -}}
+    {%- endif -%}
+{%- endmacro -%}
+
+{%- macro render_value(v) -%}
+    {%- if v is string -%}
+        {{- v -}}
+    {%- elif v is boolean -%}
+        {{- "true" if v else "false" -}}
+    {%- elif v is none -%}
+        {{- "null" -}}
+    {%- elif v is mapping or (v is sequence and v is not string) -%}
+        {{- _json(v) -}}
+    {%- else -%}
+        {{- v -}}
+    {%- endif -%}
+{%- endmacro -%}
+
+{%- macro parse_content(content) -%}
+    {%- if content is string -%}
+        {{- content -}}
+    {%- elif content is mapping and content.get("type") == "image" -%}
+        {{- "<|vision_start|><|image|><|vision_end|>" -}}
+    {%- elif content is mapping and content.get("type") == "video" -%}
+        {{- "<|vision_start|><|video|><|vision_end|>" -}}
+    {%- elif content is mapping and content.get("type") == "text" -%}
+        {{- (content.get("text") or "") | string -}}
+    {%- elif content is mapping -%}
+        {{- _json(content) -}}
+    {%- elif content is iterable -%}
+        {%- set _ns = namespace(result="") -%}
+        {%- for item in content -%}
+            {%- if item is string -%}
+                {%- set _ns.result = _ns.result + item -%}
+            {%- elif item is mapping and item.get("type") == "image" -%}
+                {%- set _ns.result = _ns.result + "<|vision_start|><|image|><|vision_end|>" -%}
+            {%- elif item is mapping and item.get("type") == "video" -%}
+                {%- set _ns.result = _ns.result + "<|vision_start|><|video|><|vision_end|>" -%}
+            {%- elif item is mapping and item.get("type") == "text" -%}
+                {%- set _ns.result = _ns.result + ((item.get("text") or "") | string) -%}
+            {%- else -%}
+                {%- set _ns.result = _ns.result + _json(item) -%}
+            {%- endif -%}
+        {%- endfor -%}
+        {{- _ns.result -}}
+    {%- elif content is not none -%}
+        {{- _json(content) -}}
+    {%- endif -%}
+{%- endmacro -%}
+
+{%- macro render_tool_calls(tool_calls) -%}
+    {%- for tool_call in tool_calls -%}
+        {%- if not loop.first -%}{{- "\n\n" -}}{%- endif -%}
+        {%- set func = tool_call["function"] if "function" in tool_call else tool_call -%}
+        {%- set func_args = func.get("arguments") -%}
+        {%- if func_args is string and (func_args | trim) not in ["", "{}", "null"] -%}
+            {{- raise_exception("Tool call arguments must be a mapping, got a JSON-encoded string: parse arguments with json.loads() before applying the chat template") -}}
+        {%- endif -%}
+        {{- "<tool_call>\n<function=" + func["name"] + ">\n" -}}
+        {%- if func_args is mapping -%}
+            {%- for arg_name, arg_value in func_args.items() -%}
+                {{- "<parameter=" + arg_name + ">\n" + render_value(arg_value) + "\n</parameter>\n" -}}
+            {%- endfor -%}
+        {%- endif -%}
+        {{- "</function>\n</tool_call>" -}}
+    {%- endfor -%}
+{%- endmacro -%}
+
+{%- macro tool_to_json(tool) -%}
+    {%- set fn = tool.function if tool.function is defined else tool -%}
+    {%- set ns_t = namespace(first=true) -%}
+    {{- "{" -}}
+    {%- for k, v in fn.items() -%}
+        {%- if k != "defer_loading" -%}
+            {%- if not ns_t.first -%}{{- ", " -}}{%- endif -%}
+            {%- set ns_t.first = false -%}
+            {{- _json(k) -}}{{- ": " -}}{{- _json(v) -}}
+        {%- endif -%}
+    {%- endfor -%}
+    {{- "}" -}}
+{%- endmacro -%}
+
+{%- macro is_tool_reference(item) -%}
+    {{- "1" if item is mapping and item.get("type") == "tool_reference" else "" -}}
+{%- endmacro -%}
+
+{%- macro referenced_tool_to_json(name) -%}
+    {%- set _ns = namespace(found=none) -%}
+    {%- for tool in (tools or []) -%}
+        {%- set fn = tool.function if tool.function is defined else tool -%}
+        {%- if fn.name == name -%}
+            {%- set _ns.found = fn -%}
+        {%- endif -%}
+    {%- endfor -%}
+    {%- if _ns.found is none -%}
+        {{- raise_exception("Tool reference '" + name | string + "' not found in available tools. Every tool referenced by a tool_reference must be in `tools` on every request.") -}}
+    {%- endif -%}
+    {{- tool_to_json(_ns.found) -}}
+{%- endmacro -%}
+
+{%- macro render_tool_response(content) -%}
+    {%- if content is string and "<tool_response>" in content -%}
+        {{- content -}}
+    {%- else -%}
+    {{- "<tool_response>\n" -}}
+    {%- if content is string -%}
+        {{- content -}}
+    {%- elif content is mapping -%}
+        {{- parse_content(content) -}}
+    {%- elif content is iterable -%}
+        {%- for item in content -%}
+            {%- if not loop.first -%}{{- "\n" -}}{%- endif -%}
+            {%- if is_tool_reference(item) -%}
+                {%- if loop.first or not is_tool_reference(loop.previtem) -%}
+                    {{- "<additional_tools>\n" -}}
+                {%- endif -%}
+                {{- referenced_tool_to_json(item.name) -}}
+                {%- if loop.last or not is_tool_reference(loop.nextitem) -%}
+                    {{- "\n</additional_tools>" -}}
+                {%- endif -%}
+            {%- elif item is mapping and item.result is defined and item.result is mapping and item.result.tools is defined -%}
+                {{- "<additional_tools>\n" -}}
+                {%- set _tl = item.result.tools -%}
+                {%- if _tl is string -%}
+                    {{- _tl -}}
+                {%- elif _tl is mapping -%}
+                    {{- tool_to_json(_tl) -}}
+                {%- else -%}
+                    {%- for t in _tl -%}
+                        {%- if not loop.first -%}{{- "\n" -}}{%- endif -%}
+                        {{- tool_to_json(t) -}}
+                    {%- endfor -%}
+                {%- endif -%}
+                {{- "\n</additional_tools>" -}}
+            {%- else -%}
+                {{- parse_content(item) -}}
+            {%- endif -%}
+        {%- endfor -%}
+    {%- elif content is not none -%}
+        {{- _json(content) -}}
+    {%- endif -%}
+    {{- "\n</tool_response>" -}}
+    {%- endif -%}
+{%- endmacro -%}
+
+{%- set ns = namespace(system_prompt="", last_user_index=-1) -%}
+{%- if messages and 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 tools_ns = namespace(lines=[]) -%}
+    {%- for tool in tools -%}
+        {%- set fn = tool.function if tool.function is defined else tool -%}
+        {%- set _dyn = (fn.defer_loading is defined and fn.defer_loading) or (tool.defer_loading is defined and tool.defer_loading) -%}
+        {%- if not _dyn -%}
+            {%- set tools_ns.lines = tools_ns.lines + [tool_to_json(fn)] -%}
+        {%- endif -%}
+    {%- endfor -%}
+    {%- if tools_ns.lines -%}
+        {%- set ns.system_prompt = ns.system_prompt + ("\n\n" if ns.system_prompt else "") + "<tools>\n" + (tools_ns.lines | join("\n")) + "\n</tools>" -%}
+    {%- endif -%}
+{%- 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 -%}
+{%- set carry = namespace(pending=[]) -%}
+{%- for message in messages -%}
+    {%- set _next = messages[loop.index0 + 1] if not loop.last else none -%}
+    {%- set _merge = message.role == "tool" and not message.get("additional_tools")
+        and _next is not none and _next.role == "tool" and not _next.get("additional_tools")
+        and message.get("tool_call_id") and _next.get("tool_call_id") == message.get("tool_call_id") -%}
+    {%- set _items = [] -%}
+    {%- if message.role == "tool" and not message.get("additional_tools") -%}
+        {%- set _c = message.get("content") -%}
+        {%- if _c is string -%}
+            {%- set _items = [{"type": "text", "text": _c}] if _c else [] -%}
+        {%- elif _c is mapping -%}
+            {%- set _items = [_c] -%}
+        {%- elif _c is iterable -%}
+            {%- set _items = _c | list -%}
+        {%- elif _c is not none -%}
+            {%- set _items = [_c] -%}
+        {%- endif -%}
+    {%- endif -%}
+    {%- if _merge -%}
+        {%- set carry.pending = carry.pending + _items -%}
+    {%- else -%}
+    {{- "<|im_start|>" + message.role + "\n" -}}
+    {%- if message.role == "assistant" -%}
+        {%- generation -%}
+        {%- set thinking = message.thinking if message.thinking is defined else message.reasoning if message.reasoning is defined else message.reasoning_content -%}
+        {%- set keep_thinking = preserve_thinking or loop.index0 > ns.last_user_index -%}
+        {%- if thinking is defined and keep_thinking -%}
+            {{- "<think>" + (thinking or "") + "</think>" -}}
+        {%- elif keep_thinking and "</think>" not in (message.get("content") if message.get("content") is string else "") -%}
+            {{- "<think></think>" -}}
+        {%- endif -%}
+        {%- set _cfm_tag = "CONTINUE_FINAL_MESSAGE_TAG " -%}
+        {%- set _has_cfm = false -%}
+        {%- set content = "" -%}
+        {%- if message.get("content") -%}
+            {%- set content = parse_content(message.content) -%}
+        {%- endif -%}
+        {%- if not keep_thinking -%}
+            {%- if "</think>" in content -%}
+                {%- set content = content.split("</think>")[-1] | trim -%}
+            {%- endif -%}
+            {%- set content = "<think></think>" + content -%}
+        {%- endif -%}
+        {%- if content.endswith(_cfm_tag) -%}
+            {%- set _has_cfm = true -%}
+            {%- set _trunc_len = (content | length) - (_cfm_tag | length) -%}
+            {%- set content = content[:_trunc_len] -%}
+        {%- endif -%}
+        {{- content -}}
+        {%- if message.tool_calls -%}
+            {{- render_tool_calls(message.tool_calls) -}}
+        {%- endif -%}
+        {%- if _has_cfm -%}
+            {{- _cfm_tag -}}
+        {%- endif -%}
+        {{- "<|im_end|>\n" -}}
+        {%- endgeneration -%}
+    {%- elif message.role == "tool" -%}
+        {%- if message.get("additional_tools") -%}
+            {%- set _at = message["additional_tools"] -%}
+            {%- if _at is mapping or (_at is sequence and _at is not string) -%}
+                {%- set _src = _at -%}
+            {%- else -%}
+                {%- set _src = message.get("content") -%}
+            {%- endif -%}
+            {%- if _src is string and "<tool_response>" in _src -%}
+                {{- _src -}}
+            {%- elif _src is string and "<additional_tools>" in _src -%}
+                {{- "<tool_response>\n" + _src + "\n</tool_response>" -}}
+            {%- elif _src -%}
+                {{- "<tool_response>\n<additional_tools>\n" -}}
+                {%- if _src is string -%}
+                    {{- _src -}}
+                {%- elif _src is mapping -%}
+                    {{- tool_to_json(_src) -}}
+                {%- else -%}
+                    {%- for t in _src -%}
+                        {%- if not loop.first -%}{{- "\n" -}}{%- endif -%}
+                        {{- tool_to_json(t) -}}
+                    {%- endfor -%}
+                {%- endif -%}
+                {{- "\n</additional_tools>\n</tool_response>" -}}
+            {%- endif -%}
+        {%- elif carry.pending -%}
+            {{- render_tool_response(carry.pending + _items) -}}
+            {%- set carry.pending = [] -%}
+        {%- else -%}
+            {{- render_tool_response("" if message.get("content") is none else message.get("content")) -}}
+        {%- endif -%}
+        {{- "<|im_end|>\n" -}}
+    {%- else %}
+        {%- if message.get("content") -%}
+            {{- parse_content(message["content"]) -}}
+        {%- endif -%}
+        {{- "<|im_end|>\n" -}}
+    {%- endif %}
+    {%- endif -%}
+{%- endfor -%}
+{%- if add_generation_prompt -%}
+    {{- "<|im_start|>assistant\n" -}}
+    {%- if enable_thinking -%}
+        {{- "<think>" -}}
+    {%- else -%}
+        {{- "<think></think>" -}}
+    {%- endif -%}
+{%- endif -%}

gpu-pipelined/lfm3_1_7b_decode_int8hu_block32_sym_pf64/tokenizer/special_tokens_map.json

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+{
+  "bos_token": "<|startoftext|>",
+  "eos_token": "<|im_end|>",
+  "pad_token": "<|pad|>"
+}

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+oid sha256:7e226e34bface23ccf6e495d157bf77186c1c30a7659880e1a8994db528c3701
+size 17908635

gpu-pipelined/lfm3_1_7b_decode_int8hu_block32_sym_pf64/tokenizer/tokenizer_config.json

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+{
+  "audio_out_token": "<|audio_out|>",
+  "audio_token": "<|audio|>",
+  "backend": "tokenizers",
+  "bos_token": "<|startoftext|>",
+  "eos_token": "<|im_end|>",
+  "extra_special_tokens": [],
+  "image_token": "<|image|>",
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<|pad|>",
+  "response_template": {
+    "defaults": {
+      "role": "assistant"
+    },
+    "start_anchor_pattern": "<\\|im_start\\|>assistant\\n",
+    "fields": {
+      "reasoning_content": {
+        "open_pattern": "<think>\\n?",
+        "close_pattern": "</think>\\s*",
+        "content": "text"
+      },
+      "tool_calls": {
+        "open_pattern": "<tool_call>\\s*<function=(?P<name>[^\\n>]+)>",
+        "close_pattern": "</tool_call>\\s*",
+        "repeats": true,
+        "content": "xml-inline",
+        "content_args": {
+          "tag_pattern": "<parameter=(?P<key>[^>\\n]+)>\\n?(?P<value>.*?)\\n?</parameter>(?=\\s*(?:<parameter=|</function>\\s*\\Z|\\Z))",
+          "value_parser": {
+            "name": "text",
+            "args": {
+              "strip": false
+            }
+          }
+        },
+        "transform": {
+          "type": "function",
+          "function": {
+            "name": "{name}",
+            "arguments": "{content}"
+          }
+        }
+      },
+      "content": {
+        "close_pattern": "<\\|im_end\\|>\\s*",
+        "content": "text"
+      }
+    }
+  },
+  "tokenizer_class": "TokenizersBackend",
+  "video_token": "<|video|>",
+  "vision_end_token": "<|vision_end|>",
+  "vision_start_token": "<|vision_start|>"
+}

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