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Model: aipster/DevRouter-1.5B
Source: Original Platform

.gitattributes

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README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen2.5-Coder-1.5B-Instruct
+language:
+  - en
+pipeline_tag: text-generation
+tags:
+  - router
+  - prompt-router
+  - structured-output
+  - json
+  - code
+  - qwen2.5-coder
+  - gguf
+---
+
+# DevRouter-1.5B
+
+**A tiny, fast router that turns a raw developer prompt into a single structured JSON decision.**
+
+DevRouter-1.5B reads a raw coding prompt and returns one JSON object that (1) rewrites the prompt
+into a cleaner version, (2) classifies its **intent**, **complexity**, and a suggested **route**
+(which model tier to send it to), and (3) flags **missing context** the developer should have
+included. It is meant to sit *in front of* your expensive models and make a cheap, deterministic
+triage call in ~1–3 seconds on a single consumer GPU.
+
+It is a fine-tune of **Qwen2.5-Coder-1.5B-Instruct** (Apache 2.0), distilled on a dataset of
+developer prompts labelled by a stronger teacher model.
+
+## Output schema
+
+Every response is a single JSON object with exactly these five fields:
+
+| field | type | values |
+|---|---|---|
+| `rewrite` | string | a clearer version of the prompt, preserving the original intent |
+| `intent` | enum | `debug` · `refactor` · `feature` · `explain` · `documentation` · `boilerplate` · `architecture` · `review` · `optimize` · `other` |
+| `complexity` | enum | `low` · `medium` · `high` |
+| `route` | enum | `small_local` · `medium_api` · `large_api` |
+| `missing` | array of strings | context the prompt should have included (empty if nothing) |
+
+### Example
+
+**Input (user message):**
+> My Flask app 500s on POST /upload with RequestEntityTooLarge, how do I fix it?
+
+**Output:**
+```json
+{
+  "rewrite": "I'm encountering a 500 Internal Server Error on my Flask app when handling POST /upload. The error is 'RequestEntityTooLarge'. How can I resolve this issue?",
+  "intent": "debug",
+  "complexity": "low",
+  "route": "small_local",
+  "missing": ["Flask version", "Python version"]
+}
+```
+
+## Quick start
+
+The router system prompt is **baked into the model's chat template**, so you do not need to supply a
+system prompt — just send the raw developer prompt as the user message.
+
+### Ollama
+```bash
+# from the -GGUF repo (Modelfile + DevRouter-1.5B-Q8_0.gguf)
+ollama create devrouter -f Modelfile
+ollama run devrouter "refactor this giant function into smaller ones"
+```
+
+### llama.cpp
+```bash
+llama-server -m DevRouter-1.5B-Q8_0.gguf -c 8192 -ngl 99 --parallel 1
+# then POST to /v1/chat/completions with just a user message, temperature 0
+```
+
+### Transformers
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+tok = AutoTokenizer.from_pretrained("aipster/DevRouter-1.5B")
+model = AutoModelForCausalLM.from_pretrained("aipster/DevRouter-1.5B")
+msgs = [{"role": "user", "content": "write a FastAPI POST /items endpoint with a Pydantic model"}]
+inputs = tok.apply_chat_template(msgs, add_generation_prompt=True, return_tensors="pt")
+out = model.generate(inputs, max_new_tokens=1408, do_sample=False)
+print(tok.decode(out[0][inputs.shape[1]:], skip_special_tokens=True))
+```
+
+Use **greedy decoding (`temperature=0`)** for stable, parseable JSON.
+
+## Evaluation
+
+Evaluated on a held-out, intent-stratified validation split (`val`, in-distribution) and an
+out-of-distribution split (`holdout`, no GitHub-issue sources). Metrics: rate of valid JSON
+(strict schema parse) and accuracy of `intent` / `route` / `complexity` against the teacher labels.
+
+| metric | fp16 (val / holdout) | Q8_0 GGUF (val / holdout) |
+|---|---|---|
+| JSON validity | 0.973 / 0.955 | 0.965 / 0.946 |
+| intent accuracy | 0.708 / 0.613 | 0.665 / 0.586 |
+| route accuracy | 0.739 / 0.604 | 0.719 / 0.631 |
+| complexity accuracy | 0.719 / 0.685 | 0.708 / 0.676 |
+
+Per-intent accuracy (Q8_0, val):
+
+| intent | acc | intent | acc |
+|---|---|---|---|
+| debug | 0.82 | architecture | 0.72 |
+| refactor | 0.72 | documentation | 0.56 |
+| explain | 0.73 | boilerplate | 0.64 |
+| feature | 0.58 | review | 0.43 |
+| optimize | 0.50 | | |
+
+## Performance
+
+Single RTX 3090, Q8_0 GGUF via llama.cpp (single stream):
+
+- **Generation: ~280 tokens/s** (~3.6 ms/token, constant across output lengths)
+- **Prompt eval (prefill): ~10,000–13,000 tokens/s**
+- **Latency per routing call: ~1–3 s** (up to ~5 s for the longest outputs)
+
+Throughput scales further with batching/concurrency.
+
+## Limitations
+
+- **No PII detection.** An earlier schema included a PII flag; it was removed from v1.1 because the
+  training data had too few PII-positive examples (~2.4%) to learn it reliably. Do **not** use this
+  model for privacy/safety filtering. (Planned for a future data-focused release.)
+- **Weaker on rare intents.** `review` and `documentation` are under-represented and noisier in the
+  training data, and accuracy on them is lower.
+- **Source bias / OOD gap.** Training prompts skew heavily toward GitHub-issue-style text, so intent
+  accuracy drops ~10 points on out-of-distribution prompts. Treat `route`/`complexity` as advisory.
+- **Quantization sensitivity.** This is a small model doing strict structured output. **Q6_K and
+  below break the JSON** (validity collapses); ship **Q8_0** or **F16** only. Always validate a
+  quant before relying on it.
+
+## Training
+
+- **Base:** Qwen2.5-Coder-1.5B-Instruct (Apache 2.0)
+- **Method:** QLoRA (4-bit), rank 16, 2 epochs, effective batch 16, `train_on_responses_only`
+- **Data:** ~2.6k developer prompts, each labelled by a stronger teacher model into the 5-field
+  schema, filtered by a judge model and capped per intent. Distillation sources permit training and
+  open release of derived weights.
+
+## Intended use
+
+Pre-routing / triage of developer prompts in an LLM application: rewriting, intent/complexity
+classification, and model-tier selection. **Not** intended for safety filtering, PII detection, or
+as a general assistant.
+
+## License
+
+Apache 2.0, inherited from the base model. You are free to use, modify, and redistribute, including
+commercially.

added_tokens.json

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+  "<|vision_end|>": 151653,
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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'] }}
+    {%- else %}
+        {{- 'You are a coding prompt router. You receive raw developer prompts and return a single JSON object with these fields:\n\n- rewrite (string): Clearer version of the prompt, preserving original intent. Do not invent requirements not present in the source.\n- intent (enum): debug | refactor | feature | explain | documentation | boilerplate | architecture | review | optimize | other\n- complexity (enum): low | medium | high\n- route (enum): small_local | medium_api | large_api\n- missing (array of strings): Context the developer should have included but didn\'t. Empty array if nothing is missing.\n\nReturn ONLY valid JSON. No prose outside the JSON.' }}
+    {%- endif %}
+    {{- "\n\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>" }}
+    {%- 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' }}
+    {%- else %}
+        {{- '<|im_start|>system\nYou are a coding prompt router. You receive raw developer prompts and return a single JSON object with these fields:\n\n- rewrite (string): Clearer version of the prompt, preserving original intent. Do not invent requirements not present in the source.\n- intent (enum): debug | refactor | feature | explain | documentation | boilerplate | architecture | review | optimize | other\n- complexity (enum): low | medium | high\n- route (enum): small_local | medium_api | large_api\n- missing (array of strings): Context the developer should have included but didn\'t. Empty array if nothing is missing.\n\nReturn ONLY valid JSON. No prose outside the JSON.<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- for message in messages %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role }}
+        {%- if message.content %}
+            {{- '\n' + message.content }}
+        {%- endif %}
+        {%- for tool_call in message.tool_calls %}
+            {%- if tool_call.function is defined %}
+                {%- set tool_call = tool_call.function %}
+            {%- endif %}
+            {{- '\n<tool_call>\n{"name": "' }}
+            {{- tool_call.name }}
+            {{- '", "arguments": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- '}\n</tool_call>' }}
+        {%- endfor %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- message.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": [
+        "Qwen2ForCausalLM"
+    ],
+    "attention_dropout": 0.0,
+    "bos_token_id": 151643,
+    "torch_dtype": "bfloat16",
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+    "hidden_act": "silu",
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+    "initializer_range": 0.02,
+    "intermediate_size": 8960,
+    "layer_types": [
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+        "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"
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+    "max_position_embeddings": 32768,
+    "max_window_layers": 21,
+    "model_type": "qwen2",
+    "num_attention_heads": 12,
+    "num_hidden_layers": 28,
+    "num_key_value_heads": 2,
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+    "rms_norm_eps": 1e-06,
+    "rope_scaling": null,
+    "rope_theta": 1000000.0,
+    "sliding_window": null,
+    "tie_word_embeddings": true,
+    "unsloth_fixed": true,
+    "unsloth_version": "2026.5.9",
+    "use_cache": true,
+    "use_sliding_window": false,
+    "vocab_size": 151936
+}

generation_config.json

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+  "do_sample": true,
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+  "repetition_penalty": 1.1,
+  "temperature": 0.7,
+  "top_k": 20,
+  "top_p": 0.8,
+  "transformers_version": "4.57.6"
+}

model.safetensors

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special_tokens_map.json

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+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
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+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
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+  "eos_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|PAD_TOKEN|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.json

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+size 11422086

tokenizer_config.json

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+  "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    {%- else %}\n        {{- 'You are a coding prompt router. You receive raw developer prompts and return a single JSON object with these fields:\\n\\n- rewrite (string): Clearer version of the prompt, preserving original intent. Do not invent requirements not present in the source.\\n- intent (enum): debug | refactor | feature | explain | documentation | boilerplate | architecture | review | optimize | other\\n- complexity (enum): low | medium | high\\n- route (enum): small_local | medium_api | large_api\\n- missing (array of strings): Context the developer should have included but didn\\'t. Empty array if nothing is missing.\\n\\nReturn ONLY valid JSON. No prose outside the JSON.' }}\n    {%- endif %}\n    {{- \"\\n\\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    {%- else %}\n        {{- '<|im_start|>system\\nYou are a coding prompt router. You receive raw developer prompts and return a single JSON object with these fields:\\n\\n- rewrite (string): Clearer version of the prompt, preserving original intent. Do not invent requirements not present in the source.\\n- intent (enum): debug | refactor | feature | explain | documentation | boilerplate | architecture | review | optimize | other\\n- complexity (enum): low | medium | high\\n- route (enum): small_local | medium_api | large_api\\n- missing (array of strings): Context the developer should have included but didn\\'t. Empty array if nothing is missing.\\n\\nReturn ONLY valid JSON. No prose outside the JSON.<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n        {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role }}\n        {%- if message.content %}\n            {{- '\\n' + message.content }}\n        {%- endif %}\n        {%- for tool_call in message.tool_calls %}\n            {%- if tool_call.function is defined %}\n                {%- set tool_call = tool_call.function %}\n            {%- endif %}\n            {{- '\\n<tool_call>\\n{\"name\": \"' }}\n            {{- tool_call.name }}\n            {{- '\", \"arguments\": ' }}\n            {{- tool_call.arguments | tojson }}\n            {{- '}\\n</tool_call>' }}\n        {%- endfor %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- message.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 %}\n"
+}