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Model: kstorm77/quick-add-qwen3-0.6b Source: Original Platform
2026-06-11 13:40:16 +08:00
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--- a/Qwen3-0.6B.Q6_K.gguf
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+version https://git-lfs.github.com/spec/v1
+oid sha256:e54f5fde068cb777a82f03e95e399cb8b7a5df00ae0f60343e1cae72241c1204
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--- a/README.md
+++ b/README.md
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+---
+base_model: Qwen/Qwen3-0.6B
+library_name: transformers
+pipeline_tag: text-generation
+language:
+- en
+- da
+tags:
+- on-device
+- json-extraction
+- qwen3
+license: apache-2.0
+---
+
+# quick-add-qwen3-0.6b
+
+A small **text-only** model for on-device use (`unified_life_hub`) that turns short EN/DK text
+into structured JSON. One model serves **two tasks**, selected by a leading **tag** in the user
+message. OCR is a separate upstream step — this model never sees images.
+
+Full fine-tune of `Qwen/Qwen3-0.6B` (no LoRA). Deployable as `Qwen3-0.6B.Q4_K_M.gguf` (~379 MB,
+llama.cpp / Ollama) or the HF weights here. Held-out fitness: valid JSON **99.9%**, exact
+**81.5%**, item-F1 **89.3%** (`[event_extract]` exact 84.3% / F1 93.7%).
+
+## ⚠️ Dates are emitted VERBATIM — the host resolves them
+
+`[event_extract]` returns each event's date/time **exactly as written** in the source
+("den 5. november kl 14", "next Thursday", "5/5 at 18", "Sct. Hans kl 9") — it does **NOT**
+convert to absolute dates. **Your app resolves** the phrase to an absolute datetime using the
+`Today is YYYY-MM-DD` line (kept in the input as the anchor) + a locale-keyed resolver. Tokens
+to handle: DK `den D. <month>` / `den D/M` / `på <weekday>` / `Sct. Hans`; EN `<Month> D` / `D/M`
+/ `next <weekday>`. Recurring lines combine the line's date with each group's time
+(e.g. `7/6 at 11:15`).
+
+## System prompt (use VERBATIM — the model is conditioned on this exact text)
+
+```
+You turn the user's text into JSON. The message begins with a mode tag.
+
+[capture] — a short note typed by the user. Split it into items and classify each as "task", "event", or "note". Keep any time reference verbatim, fuzzy is fine (tomorrow, fredag kl 14, frokost, på torsdage). Refer to people by role/name as written. Output:
+{"items":[{"type":"task|event|note","title":"...","when"?:"...","where"?:"...","priority"?:"urgent","recurring"?:true}]}
+
+[event_extract] — a longer text, often an OCR'd chat or screenshot, that starts with "Today is YYYY-MM-DD". Extract ONLY upcoming calendar EVENTS. Keep each event's date and time EXACTLY as written in the source (verbatim) — do NOT resolve to an absolute date; the "Today is" line is context only. Ignore chit-chat, to-dos, and reference facts. Output:
+{"items":[{"type":"event","title":"...","when":"<date/time exactly as written>","when_end"?:"<as written>","where"?:"..."}]}
+
+Always output ONLY the JSON object — no prose, no markdown. Preserve the input's language in titles. If nothing fits, output {"items":[]}.
+```
+
+## User message = tag + input
+
+| task | user message | output |
+|---|---|---|
+| `[capture]` | `[capture] <short note>` | `{"items":[{type:task\|event\|note, title, when?(verbatim), where?, priority?:"urgent", recurring?:true}]}` |
+| `[event_extract]` | `[event_extract] Today is YYYY-MM-DD\n<OCR'd text>` | `{"items":[{type:"event", title, when:"<as written>", when_end?, where?}]}` — future-only, verbatim date, chit-chat ignored |
+
+Examples:
+- `[capture] Call mom tomorrow` → `{"items":[{"type":"task","title":"Call mom","when":"tomorrow"}]}`
+- `[capture] Nice weather today` → `{"items":[]}`
+- `[event_extract] Today is 2026-04-01\nMette: Birthday party on 5/5 at 18 at Café Nord` →
+  `{"items":[{"type":"event","title":"Birthday party","when":"5/5 at 18","where":"Café Nord"}]}`
+  → host resolves `5/5 at 18` + anchor `2026-04-01` → `2026-05-05 18:00`.
+
+## Inference
+
+- Greedy (deterministic) decoding; stop on `<|im_end|>`.
+- **`max_new_tokens` ≥ 768** (a chunked recurring-event block can emit ~16 events / ~600 tokens;
+  a smaller budget truncates into invalid JSON).
+- The model prefixes an **empty thinking block** (`<think>\n\n</think>`). **Strip up to and
+  including `</think>`**, then parse the JSON. Untagged input defaults to `[capture]`.
+
+## Chunking (host responsibility)
+
+Chunk long input into ~2000-char fragments, call once per chunk, each **re-prefixed** with
+`[event_extract] Today is YYYY-MM-DD\n`. The model extracts only events fully inside the chunk
+and returns `{"items":[]}` otherwise. Merge per-chunk `items`; de-dupe on `(title, when)`.
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+tok = AutoTokenizer.from_pretrained("kstorm77/quick-add-qwen3-0.6b")
+model = AutoModelForCausalLM.from_pretrained("kstorm77/quick-add-qwen3-0.6b", dtype=torch.bfloat16, device_map="auto")
+msgs = [{"role": "system", "content": SYSTEM}, {"role": "user", "content": "[capture] Call mom tomorrow"}]
+ids = tok.apply_chat_template(msgs, add_generation_prompt=True, return_tensors="pt").to(model.device)
+out = tok.decode(model.generate(ids, max_new_tokens=768, do_sample=False)[0][ids.shape[1]:], skip_special_tokens=True)
+# strip up to </think>, then json.loads
+```
--- a/chat_template.jinja
+++ b/chat_template.jinja
@@ -0,0 +1,99 @@
+{%- 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 %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for forward_message in messages %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- set message = messages[index] %}
+    {%- set current_content = message.content if message.content is defined and message.content is not none else '' %}
+    {%- set tool_start = '<tool_response>' %}
+    {%- set tool_start_length = tool_start|length %}
+    {%- set start_of_message = current_content[:tool_start_length] %}
+    {%- set tool_end = '</tool_response>' %}
+    {%- set tool_end_length = tool_end|length %}
+    {%- set start_pos = (current_content|length) - tool_end_length %}
+    {%- if start_pos < 0 %}
+        {%- set start_pos = 0 %}
+    {%- endif %}
+    {%- set end_of_message = current_content[start_pos:] %}
+    {%- if ns.multi_step_tool and message.role == "user" and not(start_of_message == tool_start and end_of_message == tool_end) %}
+        {%- set ns.multi_step_tool = false %}
+        {%- set ns.last_query_index = index %}
+    {%- endif %}
+{%- endfor %}
+{%- for message in messages %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {%- set m_content = message.content if message.content is defined and message.content is not none else '' %}
+        {%- set content = m_content %}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is defined and message.reasoning_content is not none %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- else %}
+            {%- if '</think>' in m_content %}
+                {%- set content = (m_content.split('</think>')|last).lstrip('\n') %}
+                {%- set reasoning_content = (m_content.split('</think>')|first).rstrip('\n') %}
+                {%- set reasoning_content = (reasoning_content.split('<think>')|last).lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- if loop.index0 > ns.last_query_index %}
+            {%- if loop.last or (not loop.last and (not reasoning_content.strip() == '')) %}
+                {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
+            {%- else %}
+                {{- '<|im_start|>' + message.role + '\n' + content }}
+            {%- endif %}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- endif %}
+        {%- 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' }}
+        {{- 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' }}
+    {%- if enable_thinking is defined and enable_thinking is false %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- endif %}
+{%- endif %}
--- a/config.json
+++ b/config.json
@@ -0,0 +1,66 @@
+{
+  "architectures": [
+    "Qwen3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": null,
+  "dtype": "bfloat16",
+  "eos_token_id": 151645,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "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"
+  ],
+  "max_position_embeddings": 40960,
+  "max_window_layers": 28,
+  "model_name": "unsloth/Qwen3-0.6B",
+  "model_type": "qwen3",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 8,
+  "pad_token_id": 151669,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "rope_theta": 1000000,
+    "rope_type": "default"
+  },
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "transformers_version": "5.5.0",
+  "unsloth_fixed": true,
+  "unsloth_version": "2026.6.1",
+  "use_cache": false,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}
--- a/generation_config.json
+++ b/generation_config.json
@@ -0,0 +1,13 @@
+{
+  "do_sample": true,
+  "eos_token_id": [
+    151645,
+    151643
+  ],
+  "max_length": 40960,
+  "pad_token_id": 151669,
+  "temperature": 0.6,
+  "top_k": 20,
+  "top_p": 0.95,
+  "transformers_version": "5.5.0"
+}
--- a/model.safetensors
+++ b/model.safetensors
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+version https://git-lfs.github.com/spec/v1
+oid sha256:9cb3ecd3be078378d4183532fb24cacaae00f106c992a8d13bff9bdea73a17c3
+size 1192135096
--- a/tokenizer.json
+++ b/tokenizer.json
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:45c4ffda6666cf6d75d0b1f961f25964e2a52a62e78aaecb2f458e9ba9824112
+size 11422840
--- a/tokenizer_config.json
+++ b/tokenizer_config.json
@@ -0,0 +1,233 @@
+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "is_local": false,
+  "model_max_length": 40960,
+  "pad_token": "<|PAD_TOKEN|>",
+  "padding_side": "left",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "151644": {
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+      "lstrip": false,
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+    "151645": {
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+      "lstrip": false,
+      "rstrip": false,
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+    },
+    "151646": {
+      "content": "<|object_ref_start|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "151647": {
+      "content": "<|object_ref_end|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
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+    },
+    "151648": {
+      "content": "<|box_start|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
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+    "151649": {
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+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": false
+    },
+    "151658": {
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+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
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+      "single_word": false,
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+      "rstrip": false,
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+    "151660": {
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+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": false
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+      "lstrip": false,
+      "rstrip": false,
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+      "normalized": false,
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+      "normalized": false,
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+  }
+}