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Model: CodeStrux-Tech/tac-1
Source: Original Platform

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LICENSE

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README.md

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+---
+license: apache-2.0
+language:
+  - es
+base_model: Qwen/Qwen3-4B-Instruct-2507
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+  - address-parsing
+  - structured-output
+  - costa-rica
+  - geocoding
+  - qwen3
+---
+
+# tac-1 — Costa Rican reference-point address parser
+
+## What is tac-1
+
+Costa Rica has no street-address system. Addresses are reference-point narratives — "del antiguo higuerón de San Pedro, 100 metros sur" or "de la esquina noroeste del Mercado Central, 200 metros norte, casa esquinera." tac-1 parses these into a structured, leg-based JSON record. It performs **parsing only**: geometry (resolving the anchor point to coordinates and walking the OSM street graph along each leg) belongs to a separate deterministic grounder (the companion `tico` package, not part of this model release).
+
+## Architecture
+
+tac-1 is a hybrid system. This model extracts the structured address fields (anchor name, anchor type, and a list of legs with direction and distance). The `tico` package then grounds the parse by walking the OSM street graph — it resolves the anchor to a coordinate via `resolve_anchor`, then traces each leg along the graph using the same geometry core that generated the training data.
+
+## Evaluation
+
+### gold-47 vs teacher
+
+| metric | tac-1 (bf16) | tac-1 (FP8) | teacher gpt-4.1 |
+|---|---|---|---|
+| parse rate | 1.000 | 1.000 | 1.000 |
+| anchor_name F1 | 0.979 | 0.979 | 0.872 |
+| direction F1 | 0.995 | 0.984 | 1.000 |
+| distance F1 | 0.995 | 0.984 | 1.000 |
+| perfect-anchor ≤250 m | 93.6% | 93.6% | 93.6% |
+| perfect-anchor median | 0.0 m | 0.0 m | 0.0 m |
+| gazetteer ≤250 m | 80.9% | 80.9% | 83.0% |
+
+**Headline:** anchor_name F1 beats the gpt-4.1 teacher, with zero geographic overfit on never-trained districts.
+
+### heldout-805
+
+| metric | tac-1 (bf16) |
+|---|---|
+| parse rate | 1.000 |
+| anchor_name F1 | 1.000 |
+| direction F1 | 1.000 |
+| distance F1 | 1.000 |
+| perfect-anchor median | 89.5 m |
+| perfect-anchor ≤250 m | 81.0% |
+| gazetteer median | 148.8 m |
+| gazetteer ≤250 m | 65.0% |
+
+Grounding-baseline medians on heldout-805: hybrid_walk 143.8 m vs calibrated_project 198.7 m vs naive_project 201.9 m (the graph walk beats projection on unseen geography).
+
+The three never-trained districts (grecia, curridabat, go-guadalupe) show anchor_name/direction/distance F1 all at 1.000 — zero geographic overfit.
+
+## Quickstart
+
+```bash
+vllm serve CodeStrux-Tech/tac-1 --served-model-name tac-1 --max-model-len 4096
+# On hosts without nvcc, disable the FlashInfer sampler JIT:
+#   VLLM_USE_FLASHINFER_SAMPLER=0 vllm serve ...
+```
+
+```python
+from tico.extractor.clients.vllm import VLLMExtractor
+
+extractor = VLLMExtractor()  # VLLM_BASE_URL=http://localhost:8000/v1, TICO_VLLM_MODEL=tac-1
+addr = extractor.extract("del antiguo higuerón de San Pedro, 100 metros sur")
+print(addr.model_dump_json(indent=2))
+```
+
+## Limitations
+
+- **confidence is a constant 0.0** — uncalibrated; do not consume this value.
+- **anchor lat/lon/osm_id are always null by design** — coordinates belong to the grounder's `resolve_anchor`, not the model.
+- **Spanish/Costa-Rica-specific** — the model was trained and evaluated exclusively on Costa Rican Spanish reference-point addresses.
+- **Remaining system headroom is gazetteer/calibration coverage, not the model** — the extractor is at or near ceiling on the evaluation sets; further accuracy gains require broader OSM ingestion and calibration.
+
+## Training
+
+- **Base model:** Qwen/Qwen3-4B-Instruct-2507
+- **Method:** QLoRA (r=16, α=32)
+- **Learning rate:** 2e-4
+- **Epochs:** 2
+- **Max sequence length:** 4096
+- **Steps:** 692
+- **Final train loss:** 0.043
+- **Hardware:** ~2 h 50 m on an RTX 4080 16 GB
+- **Stack:** unsloth 2025.11.1 / transformers 4.57.2 / trl 0.23.0
+- **Corpus:** `CodeStrux-Tech/tac-1-corpus` — 5,532 train examples (seed 0), 805 heldout examples (seed 1); `--max-legs 4`; 22 districts ingested, 19,042 POIs, 11 griddable; holdout districts grecia, curridabat, go-guadalupe excluded from training.
+
+### Training data attribution
+
+Contains information from OpenStreetMap (https://www.openstreetmap.org/copyright), which is made available under the Open Database License (ODbL) 1.0. © OpenStreetMap contributors.
+
+**Licensing.** The tac-1 corpus is a derivative database of OpenStreetMap and is released under the Open Database License (ODbL) 1.0, with attribution: © OpenStreetMap contributors (https://www.openstreetmap.org/copyright). The tac-1 model weights are a produced work trained on that corpus and are released under Apache-2.0; the corpus's ODbL provenance is disclosed in every model card. Code is Apache-2.0 (LICENSE); data is ODbL (DATA_LICENSE); see NOTICE. Sources are OpenStreetMap + INEC/IGN + community DTA tables only — no Google or Waze data anywhere in the pipeline, training data, or release.
+
+## Related
+
+- [`CodeStrux-Tech/tac-1-fp8-dynamic`](https://huggingface.co/CodeStrux-Tech/tac-1-fp8-dynamic) — FP8 dynamic quantization
+- [`CodeStrux-Tech/tac-1-gguf`](https://huggingface.co/CodeStrux-Tech/tac-1-gguf) — GGUF (Q5_K_M + f16) for llama.cpp / Ollama
+- [`CodeStrux-Tech/tac-1-lora`](https://huggingface.co/CodeStrux-Tech/tac-1-lora) — QLoRA adapter weights
+- [`CodeStrux-Tech/tac-1-corpus`](https://huggingface.co/CodeStrux-Tech/tac-1-corpus) — training corpus (ODbL)
+
+tac-1 is a derivative work of [Qwen/Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507), Copyright 2024 Alibaba Cloud, licensed under the Apache License, Version 2.0. The upstream LICENSE is included in this repository.

added_tokens.json

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chat_template.jinja

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+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0].role == 'system' %}
+        {{- messages[0].content + '\n\n' }}
+    {%- endif %}
+    {{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
+{%- else %}
+    {%- if messages[0].role == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- for message in messages %}
+    {%- if message.content is string %}
+        {%- set content = message.content %}
+    {%- else %}
+        {%- set content = '' %}
+    {%- endif %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
+        {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- if message.tool_calls %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if (loop.first and content) or (not loop.first) %}
+                    {{- '\n' }}
+                {%- endif %}
+                {%- if tool_call.function %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {{- '<tool_call>\n{"name": "' }}
+                {{- tool_call.name }}
+                {{- '", "arguments": ' }}
+                {%- if tool_call.arguments is string %}
+                    {{- tool_call.arguments }}
+                {%- else %}
+                    {{- tool_call.arguments | tojson }}
+                {%- endif %}
+                {{- '}\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+{%- endif %}

config.json

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+{
+    "architectures": [
+        "Qwen3ForCausalLM"
+    ],
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "torch_dtype": "bfloat16",
+    "eos_token_id": 151645,
+    "head_dim": 128,
+    "hidden_act": "silu",
+    "hidden_size": 2560,
+    "initializer_range": 0.02,
+    "intermediate_size": 9728,
+    "layer_types": [
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention"
+    ],
+    "max_position_embeddings": 262144,
+    "max_window_layers": 36,
+    "model_type": "qwen3",
+    "num_attention_heads": 32,
+    "num_hidden_layers": 36,
+    "num_key_value_heads": 8,
+    "pad_token_id": 151654,
+    "rms_norm_eps": 1e-06,
+    "rope_scaling": null,
+    "rope_theta": 5000000,
+    "sliding_window": null,
+    "tie_word_embeddings": true,
+    "transformers_version": "4.57.2",
+    "unsloth_fixed": true,
+    "unsloth_version": "2025.11.1",
+    "use_cache": true,
+    "use_sliding_window": false,
+    "vocab_size": 151936
+}

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model.safetensors.index.json

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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151661": {
+      "content": "<|fim_suffix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151662": {
+      "content": "<|fim_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151663": {
+      "content": "<|repo_name|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151664": {
+      "content": "<|file_sep|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151665": {
+      "content": "<tool_response>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151666": {
+      "content": "</tool_response>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151667": {
+      "content": "<think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151668": {
+      "content": "</think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": {},
+  "model_max_length": 262144,
+  "pad_token": "<|vision_pad|>",
+  "padding_side": "right",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null,
+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0].role == 'system' %}\n        {{- messages[0].content + '\\n\\n' }}\n    {%- endif %}\n    {{- \"# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {{- '<|im_start|>system\\n' + messages[0].content + '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n    {%- if message.content is string %}\n        {%- set content = message.content %}\n    {%- else %}\n        {%- set content = '' %}\n    {%- endif %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}\n        {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role + '\\n' + content }}\n        {%- if message.tool_calls %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if (loop.first and content) or (not loop.first) %}\n                    {{- '\\n' }}\n                {%- endif %}\n                {%- if tool_call.function %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {{- '<tool_call>\\n{\"name\": \"' }}\n                {{- tool_call.name }}\n                {{- '\", \"arguments\": ' }}\n                {%- if tool_call.arguments is string %}\n                    {{- tool_call.arguments }}\n                {%- else %}\n                    {{- tool_call.arguments | tojson }}\n                {%- endif %}\n                {{- '}\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- content }}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n{%- endif %}"
+}