| --- |
| base_model: |
| - Qwen/Qwen3-0.6B |
| - Qwen/Qwen2.5-0.5B-Instruct |
| - HuggingFaceTB/SmolLM2-360M-Instruct |
| - meta-llama/Llama-3.2-1B-Instruct |
| library_name: transformers |
| pipeline_tag: text-classification |
| tags: |
| - intent-classification |
| - tool-routing |
| - gguf |
| - onnx |
| - llama.cpp |
| - onnxruntime |
| license: other |
| --- |
| |
| # Intent Classifier — Release Models |
|
|
| Small, fine-tuned language models for routing a user request to one tool. Each |
| model returns a compact routing label, not a natural-language response. |
|
|
| The current recommended release is **v2.1 Qwen2.5-0.5B** (`v2.1-qwen2.5-0.5b`): |
| it achieved 99.9% test accuracy in the v2.1 evaluation. |
|
|
| ## Choose a release |
|
|
| | Version | Scope | Recommended completed models | |
| | --- | --- | --- | |
| | v2.1 | Full 10k positional-ID DoRA+ experiments, configuration D | Qwen3-0.6B: 99.8% test; Qwen2.5-0.5B: 99.9% test; SmolLM2-360M: 99.7% test. **Recommended: Qwen2.5-0.5B**—the highest-scoring and fastest of the three (253 ms P50). | |
| | v2.0 | 1k positional-ID experiment matrix (800/100/100) | **DoRA+ Qwen3-0.6B D** (99% validation, 100% test) and **DoRA+ Llama3.2-1B C** (96% validation, 100% test). | |
| | v1.0 | Initial 1k name-output experiments | **LoRA Qwen3-0.6B C** (99% test) and **LoRA Llama3.2-1B C** (100% test). | |
|
|
| Use v2.1 or v2.0 when your application can map a positional ID back to its |
| tool. Use v1.0 only when your integration requires the model to emit a tool |
| name directly. |
|
|
| ## Output contract |
|
|
| These are generative routing models. Build the prompt as plain text exactly in |
| the relevant format below, tokenize that text directly, and read only the |
| generated continuation. Do **not** wrap the prompt in the base model's chat |
| template: the examples below are the complete prompt content before any model |
| tokenizer adds its own special or chat-template tokens. |
|
|
| | Release | Native output | No-tool output | Evaluator behavior | |
| | --- | --- | --- | --- | |
| | v1.0 | Tool name, such as `call_handler` | `none` | Used directly as the canonical tool name. | |
| | v2.x | Positional tool ID, such as `d` | `-` | Convert the ID to the tool name from the prompt's tool list before scoring or invoking the tool. | |
|
|
| ### Example: v1.0 (tool-name output) |
|
|
| For `Call my wife.`, the expected raw model output is `call_handler`. |
|
|
| ```text |
| You are a tool router. |
| |
| Rules: |
| - Return only the tool name. |
| - Return "none" if no tool matches. |
| - Do not explain. |
| |
| Available Tools: |
| Name: health_monitor |
| Description: Monitors driver biometrics such as heart rate, blood oxygen, and cumulative fatigue score from wearables. |
| |
| Name: insurance_claims |
| Description: Initiates, documents, and tracks vehicle insurance claims including photo upload and damage assessment. |
| |
| Name: nav_route_planner |
| Description: Plans optimal routes, provides turn-by-turn navigation, and recalculates routes around obstacles. |
| |
| Name: call_handler |
| Description: Initiates, receives, holds, and terminates hands-free phone calls. |
| |
| Name: remote_vehicle_lock |
| Description: Remotely locks or unlocks vehicle doors, boot, and windows and reports current lock state. |
| |
| User Request: |
| Call my wife. |
| |
| Selected Tool: |
| ``` |
|
|
| ### Example: v2.x (positional-ID output) |
|
|
| For the same request, `call_handler` is the fourth displayed tool, so the |
| expected raw model output is `d`. Convert `d` back to `call_handler` using the |
| tool list before calculating accuracy or calling the tool. |
|
|
| ```text |
| You are a tool router. |
| |
| Available tools are listed with id, name, and description. |
| |
| Rules: |
| - Return only the tool id. |
| - Use the id from the available tools list. |
| - Return "-" if no tool matches. |
| - Do not explain. |
| |
| Available Tools: |
| ID | Name | Description |
| a | health_monitor | Monitors driver biometrics such as heart rate, blood oxygen, and cumulative fatigue score from wearables. |
| b | insurance_claims | Initiates, documents, and tracks vehicle insurance claims including photo upload and damage assessment. |
| c | nav_route_planner | Plans optimal routes, provides turn-by-turn navigation, and recalculates routes around obstacles. |
| d | call_handler | Initiates, receives, holds, and terminates hands-free phone calls. |
| e | remote_vehicle_lock | Remotely locks or unlocks vehicle doors, boot, and windows and reports current lock state. |
| |
| User Request: |
| Call my wife. |
| |
| Selected Tool: |
| ``` |
|
|
| ## Artifacts |
|
|
| Each release/model folder contains the same inference formats. |
|
|
| - `transformers/`: merged full-weight Transformers checkpoint in safetensors |
| format, plus tokenizer and generation configuration. |
| - `gguf/<quant>/model.gguf`: llama.cpp-compatible exports (`Q4_K_M`, `Q6_K`, |
| and `Q8_0`). |
| - `onnx/<variant>/`: ONNX Runtime exports. Keep every file in a variant folder |
| together; `model.onnx` can reference an adjacent external-data file. |
|
|
| The individual release README and `benchmark_provenance.json` record the exact |
| base-model revision, adapter configuration, prompt format, and artifact |
| provenance. |
|
|
| ## Licensing and notices |
|
|
| This is a **mixed-license repository**, so its Hugging Face metadata is marked |
| `other` rather than `apache-2.0`. Fine-tuning, merging, quantizing, and |
| exporting a model do not replace the license of its base-model weights. |
| The Llama release artifacts are **Built with Llama**. |
|
|
| | Artifacts | Upstream license | What a redistributor must do | |
| | --- | --- | --- | |
| | Qwen3-0.6B and Qwen2.5-0.5B derivatives | [Apache License 2.0](https://huggingface.co/Qwen/Qwen3-0.6B) | Comply with Apache-2.0, including its license and notice requirements. | |
| | SmolLM2-360M derivatives | [Apache License 2.0](https://huggingface.co/HuggingFaceTB/SmolLM2-360M-Instruct) | Comply with Apache-2.0, including its license and notice requirements. | |
| | Llama-3.2-1B derivatives | [Llama 3.2 Community License](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct) | Comply with the agreement and Acceptable Use Policy. Distributed copies must include the agreement and a `Notice` text file containing Meta's required attribution. | |
|
|
| For a release containing Llama artifacts, include the Llama 3.2 Community |
| License Agreement and a `Notice` file with this attribution: |
|
|
| ```text |
| Llama 3.2 is licensed under the Llama 3.2 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved. |
| ``` |
|
|
| Before publishing, also confirm that the training/evaluation data and any |
| third-party conversion code permit the intended distribution. This summary is |
| operational guidance, not legal advice. |
|
|
| ## Related repositories |
|
|
| - Training code: <https://github.com/kon171verma/intent-classifier> |
| - Inference and benchmarking: <https://github.com/kon171verma/intent-classifier-edge-inference> |
| - Experiment adapters: <https://huggingface.co/kon171verma/intent-classifier-experiments> |
|
|
