[qwen3-0.6b] auto-publish: base=Qwen/Qwen3-0.6B at 2026-05-22T22:42:56.490740+00:00

.gitattributes

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 smollm2-360m/gguf/txn-parser-smollm2-360m-Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
 smollm2-360m/gguf/txn-parser-smollm2-360m-Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
 smollm2-360m/gguf/txn-parser-smollm2-360m-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
+qwen3-0.6b/adapters/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+qwen3-0.6b/gguf/txn-parser-qwen3-0.6b-F16.gguf filter=lfs diff=lfs merge=lfs -text
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+qwen3-0.6b/gguf/txn-parser-qwen3-0.6b-Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
+qwen3-0.6b/gguf/txn-parser-qwen3-0.6b-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text

qwen3-0.6b/README.md

@@ -0,0 +1,152 @@
+---
+license: apache-2.0
+base_model: Qwen/Qwen3-0.6B
+tags:
+  - text-generation
+  - lora
+  - qlora
+  - gguf
+  - transaction-parser
+language:
+  - en
+  - hi
+library_name: peft
+---
+
+# txn-parser / qwen3-0.6b
+
+QLoRA fine-tune of [`Qwen/Qwen3-0.6B`](https://huggingface.co/Qwen/Qwen3-0.6B) for
+extracting structured transaction data (amount, currency, item, category,
+type) from free-form Indian-English / code-switched speech and text.
+
+This model lives in subfolder **`qwen3-0.6b/`** of the
+[`kartikey31/txn-parser`](https://huggingface.co/kartikey31/txn-parser) repo, alongside
+sibling fine-tunes of other base models trained on the same data.
+
+## What's in here
+
+- `qwen3-0.6b/adapters/` — PEFT LoRA adapter (rank 32). Load on top of the base model
+  with `peft.PeftModel.from_pretrained(base, "kartikey31/txn-parser", subfolder="qwen3-0.6b/adapters")`.
+- `qwen3-0.6b/gguf/` — merged GGUF builds at multiple quantization levels
+  (file names follow `txn-parser-qwen3-0.6b-<QUANT>.gguf`):
+  - [`qwen3-0.6b/gguf/txn-parser-qwen3-0.6b-F16.gguf`](https://huggingface.co/kartikey31/txn-parser/resolve/main/qwen3-0.6b/gguf/txn-parser-qwen3-0.6b-F16.gguf)  (1198.2 MB)
+  - [`qwen3-0.6b/gguf/txn-parser-qwen3-0.6b-Q4_K_M.gguf`](https://huggingface.co/kartikey31/txn-parser/resolve/main/qwen3-0.6b/gguf/txn-parser-qwen3-0.6b-Q4_K_M.gguf)  (396.7 MB)
+  - [`qwen3-0.6b/gguf/txn-parser-qwen3-0.6b-Q5_K_M.gguf`](https://huggingface.co/kartikey31/txn-parser/resolve/main/qwen3-0.6b/gguf/txn-parser-qwen3-0.6b-Q5_K_M.gguf)  (444.4 MB)
+  - [`qwen3-0.6b/gguf/txn-parser-qwen3-0.6b-Q6_K.gguf`](https://huggingface.co/kartikey31/txn-parser/resolve/main/qwen3-0.6b/gguf/txn-parser-qwen3-0.6b-Q6_K.gguf)  (495.1 MB)
+  - [`qwen3-0.6b/gguf/txn-parser-qwen3-0.6b-Q8_0.gguf`](https://huggingface.co/kartikey31/txn-parser/resolve/main/qwen3-0.6b/gguf/txn-parser-qwen3-0.6b-Q8_0.gguf)  (639.4 MB)
+
+## Training data
+
+- 93,348 teacher-labeled examples (`data/distill/train.jsonl`)
+- 300 held-out eval examples (`data/distill/eval.jsonl`)
+- Validator-gated: every row's `output` passes the project's grammar +
+  amount-parser semantic validator.
+
+## Training config
+
+| Knob | Value |
+|---|---|
+| Base model | `Qwen/Qwen3-0.6B` |
+| Method | QLoRA (4-bit) via Unsloth |
+| LoRA rank | 32 (alpha 64, dropout 0.0) |
+| Epochs | 2 |
+| Batch size (train) | 64 |
+| Grad accumulation | 2 |
+| Eval batch size | 16 |
+| Max seq length | 1024 |
+| Learning rate | 2e-4 (warmup 3%) |
+| Started | 2026-05-22T21:54:03.967900+00:00 |
+| Finished | 2026-05-22T22:42:56.089528+00:00 |
+
+## System prompt (use this EXACTLY)
+
+The model was trained with one specific system prompt and Gemma/Smol/Qwen
+chat template. If you paraphrase the prompt or skip the chat template,
+quality degrades quickly. Copy-paste this verbatim into your inference
+client (no leading/trailing whitespace, no edits):
+
+```text
+You convert voice-transcribed transaction descriptions into structured JSON.
+
+Output ONLY a JSON object with this schema, no other text:
+{"transactions":[{"amount":<number>,"currency":"INR"|"USD","item":"<lowercase singular noun phrase>","category":"<enum>","type":"expense"|"income"}]}
+
+Categories: Food, Drinks, Groceries, Transport, Shopping, Entertainment, Bills, Health, Education, Personal, Gifts, Income, Other.
+
+Rules:
+- Currency defaults to INR. Use USD only when the input explicitly says "dollars" or contains "$".
+- Amounts: "k" = ×1000, "hazaar" = ×1000, "sau" = ×100, "lakh" = ×100000. Convert number-words ("five hundred") to digits.
+- type is "expense" by default; "income" only for explicit salary, cashback, refund, gift received, payment received.
+- For disfluencies and corrections ("500 wait no 600"), output the CORRECTED amount only.
+- For ambiguous items ("that thing", "stuff"), use item "unspecified" and category "Other".
+- Item field: lowercase singular noun phrase ("uber ride", "beer", "chai" — not "Beers" or "Uber").
+- Multi-transaction inputs become multiple array entries in spoken order.
+- Category heuristics: uber/ola/auto/petrol/bus/metro → Transport; beer/wine/chai/coffee/juice → Drinks; rent/electricity/wifi/recharge/gas → Bills; movie/netflix/concert → Entertainment; doctor/medicine/hospital → Health.
+```
+
+Source of truth: [`scripts/_lib.py`](https://github.com/kartikeychoudhary/txn-parser/blob/main/scripts/_lib.py)
+constant `SYSTEM_PROMPT`. Don't retype it — pull from `_lib.py` or this README.
+
+## Download a single GGUF
+
+```bash
+huggingface-cli download kartikey31/txn-parser \
+    qwen3-0.6b/gguf/txn-parser-qwen3-0.6b-Q4_K_M.gguf \
+    --local-dir .
+```
+
+## Inference (Python, llama-cpp-python)
+
+```python
+from llama_cpp import Llama
+
+SYSTEM_PROMPT = '''You convert voice-transcribed transaction descriptions into structured JSON.
+
+Output ONLY a JSON object with this schema, no other text:
+{"transactions":[{"amount":<number>,"currency":"INR"|"USD","item":"<lowercase singular noun phrase>","category":"<enum>","type":"expense"|"income"}]}
+
+Categories: Food, Drinks, Groceries, Transport, Shopping, Entertainment, Bills, Health, Education, Personal, Gifts, Income, Other.
+
+Rules:
+- Currency defaults to INR. Use USD only when the input explicitly says "dollars" or contains "$".
+- Amounts: "k" = ×1000, "hazaar" = ×1000, "sau" = ×100, "lakh" = ×100000. Convert number-words ("five hundred") to digits.
+- type is "expense" by default; "income" only for explicit salary, cashback, refund, gift received, payment received.
+- For disfluencies and corrections ("500 wait no 600"), output the CORRECTED amount only.
+- For ambiguous items ("that thing", "stuff"), use item "unspecified" and category "Other".
+- Item field: lowercase singular noun phrase ("uber ride", "beer", "chai" — not "Beers" or "Uber").
+- Multi-transaction inputs become multiple array entries in spoken order.
+- Category heuristics: uber/ola/auto/petrol/bus/metro → Transport; beer/wine/chai/coffee/juice → Drinks; rent/electricity/wifi/recharge/gas → Bills; movie/netflix/concert → Entertainment; doctor/medicine/hospital → Health.'''
+
+llm = Llama(
+    model_path="txn-parser-qwen3-0.6b-Q4_K_M.gguf",
+    n_gpu_layers=-1, n_ctx=2048,
+)
+out = llm.create_chat_completion(
+    messages=[
+        {"role": "system", "content": SYSTEM_PROMPT},
+        {"role": "user",   "content": "200 ka samosa"},
+    ],
+    temperature=0.0,
+)
+print(out["choices"][0]["message"]["content"])
+```
+
+## Inference (CLI, llama.cpp)
+
+```bash
+./llama-cli -m txn-parser-qwen3-0.6b-Q4_K_M.gguf \
+    --grammar-file scripts/grammar.gbnf \
+    --system-prompt "$(cat system_prompt.txt)" \
+    -p "200 ka samosa" -n 256
+```
+
+## Reproduce
+
+```bash
+git clone https://github.com/kartikeychoudhary/txn-parser.git
+cd txn-parser && bash setup.sh
+python scripts/train_and_publish.py --only qwen3-0.6b
+```
+
+---
+*Auto-published by `scripts/train_and_publish.py` on 2026-05-22T22:42:56.387243+00:00.*

qwen3-0.6b/adapters/README.md

@@ -0,0 +1,210 @@
+---
+base_model: unsloth/qwen3-0.6b-unsloth-bnb-4bit
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:unsloth/qwen3-0.6b-unsloth-bnb-4bit
+- lora
+- sft
+- transformers
+- trl
+- unsloth
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.19.1

qwen3-0.6b/adapters/adapter_config.json

@@ -0,0 +1,52 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "Qwen3ForCausalLM",
+    "parent_library": "transformers.models.qwen3.modeling_qwen3",
+    "unsloth_fixed": true
+  },
+  "base_model_name_or_path": "unsloth/qwen3-0.6b-unsloth-bnb-4bit",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 64,
+  "lora_bias": false,
+  "lora_dropout": 0.0,
+  "lora_ga_config": null,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.19.1",
+  "qalora_group_size": 16,
+  "r": 32,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "down_proj",
+    "o_proj",
+    "gate_proj",
+    "q_proj",
+    "up_proj",
+    "k_proj",
+    "v_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_bdlora": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

qwen3-0.6b/adapters/adapter_model.safetensors

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+size 80792456

qwen3-0.6b/adapters/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 %}

qwen3-0.6b/adapters/tokenizer.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d7430e9138b76e93fb6f93462394d236b411111aef53cb421ba97d2691040cca
+size 11423114

qwen3-0.6b/adapters/tokenizer_config.json

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+{
+  "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": {
+      "content": "<|im_start|>",
+      "single_word": false,
+      "lstrip": false,
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