From 6c5ba69ac2d622e98f454952fa7451529fcf9c65 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Tue, 30 Jun 2026 00:09:23 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: Turhan123/astra-meal-parser Source: Original Platform --- .gitattributes | 36 +++ README.md | 208 +++++++++++++++ chat_template.jinja | 54 ++++ config.json | 70 +++++ generation_config.json | 14 + model-00001-of-00002.safetensors | 3 + model-00002-of-00002.safetensors | 3 + model.safetensors.index.json | 441 +++++++++++++++++++++++++++++++ tokenizer.json | 3 + tokenizer_config.json | 202 ++++++++++++++ 10 files changed, 1034 insertions(+) create mode 100644 .gitattributes create mode 100644 README.md create mode 100644 chat_template.jinja create mode 100644 config.json create mode 100644 generation_config.json create mode 100644 model-00001-of-00002.safetensors create mode 100644 model-00002-of-00002.safetensors create mode 100644 model.safetensors.index.json create mode 100644 tokenizer.json create mode 100644 tokenizer_config.json diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..52373fe --- /dev/null +++ b/.gitattributes @@ -0,0 +1,36 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text +tokenizer.json filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000..8ea557e --- /dev/null +++ b/README.md @@ -0,0 +1,208 @@ +--- +license: other +license_name: qwen-research +license_link: https://huggingface.co/Qwen/Qwen2.5-3B-Instruct/blob/main/LICENSE +base_model: Qwen/Qwen2.5-3B-Instruct +language: +- tr +- en +library_name: transformers +pipeline_tag: text-generation +tags: +- unsloth +- qwen2.5 +- lora +- sft +- meal-parsing +- nutrition +- calorie-estimation +- turkish +- structured-output +- json +--- + +# 🥗 Astra Meal Parser (v1) + +A fine-tuned **Qwen2.5-3B-Instruct** model that reads a free-text meal description in +**Turkish or English** and turns it into a clean, structured list of food items and their +amounts — ready to feed into a deterministic nutrition calculator. + +The model **does not** estimate calories or macros itself. It only parses. This is a +deliberate design choice (see *Why parsing only?* below) that keeps nutrition accuracy +high and easy to maintain. + +``` +"2 yumurta, 100g tavuk göğsü ve 1 muz" + │ + ▼ (this model — parsing) +{"items": [ + {"name": "Yumurta", "amount": "2 adet"}, + {"name": "Tavuk Göğsü", "amount": "100g"}, + {"name": "Muz", "amount": "1 adet"} +]} + │ + ▼ (nutrition table + calculator — not part of this model) +{ totalCalories, totalProtein, totalCarbs, totalFat, items[...] } +``` + +- **Developed by:** Turhan Göksu +- **Model type:** Causal LM adapter merged into base weights (Qwen2.5-3B) +- **Languages:** Turkish, English, and mixed/code-switched input +- **Finetuned from:** [Qwen/Qwen2.5-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct) + +## Why parsing only? + +An earlier version asked the model to output calories and macros directly. It plateaued at +~25% calorie error with a systematic overestimation bias: a language model cannot reliably +memorize accurate per-food nutrition values, especially for foods with high natural variance. + +Splitting the problem fixed this. The model now does the one thing language models are good +at — understanding messy natural language — and a static nutrition table + a small +calculator handle the arithmetic deterministically. Result: calorie error dropped from ~25% +to ~3%, and any remaining error is fixable by editing the table, **without retraining**. + +## Output format + +The model is trained to return **only** a strict JSON object: + +```json +{"items": [{"name": "string", "amount": "string"}]} +``` + +No prose, no markdown, no macros — just the JSON. + +## System prompt + +Use this exact system prompt for best results: + +``` +You are a meal parser. Extract every food item and its amount from the user's meal +description (Turkish or English). Return ONLY a strict JSON object of the form +{"items": [{"name": string, "amount": string}]}. No macros, no calories, no +conversational text, no markdown, only valid JSON. +``` + +## Uses + +### Direct use +- Meal logging / calorie tracking apps where users type meals in natural language. +- Bilingual and code-switched input such as `"200g grilled chicken ve 1 kase pirinç"`. +- A drop-in front end for a deterministic nutrition pipeline. + +### Out-of-scope use +- **Standalone nutrition estimation.** This model only extracts items and amounts; it does + not produce calories or macros on its own. +- **Medical or dietary prescriptions.** Output is informational, not medical advice. +- **Open-ended conversation.** The model is specialized for structured parsing and is not + intended as a general assistant. + +## How to get started + +> **Note on inference.** This is a custom merged model and is **not served by the free +> Hugging Face Serverless Inference API**. Run it locally with `transformers`, convert it to +> GGUF for on-device / `llama.cpp` use, or deploy a dedicated Inference Endpoint. + +```python +import json +from transformers import AutoModelForCausalLM, AutoTokenizer + +model_id = "Turhan123/astra-meal-parser" # pin a version with revision="v1" +tokenizer = AutoTokenizer.from_pretrained(model_id, revision="v1") +model = AutoModelForCausalLM.from_pretrained(model_id, revision="v1", device_map="auto") + +SYSTEM = ( + "You are a meal parser. Extract every food item and its amount from the user's " + "meal description (Turkish or English). Return ONLY a strict JSON object of the form " + '{"items": [{"name": string, "amount": string}]}. ' + "No macros, no calories, no conversational text, no markdown, only valid JSON." +) + +def parse(meal: str): + messages = [{"role": "system", "content": SYSTEM}, + {"role": "user", "content": meal}] + ids = tokenizer.apply_chat_template(messages, add_generation_prompt=True, + return_tensors="pt").to(model.device) + out = model.generate(ids, max_new_tokens=256, do_sample=False) + text = tokenizer.decode(out[0][ids.shape[-1]:], skip_special_tokens=True) + return json.loads(text) + +print(parse("2 yumurta, 100g tavuk göğsü ve 1 muz")) +# {'items': [{'name': 'Yumurta', 'amount': '2 adet'}, ...]} +``` + +## Training + +| | | +|---|---| +| Base model | `Qwen/Qwen2.5-3B-Instruct` (4-bit QLoRA via Unsloth) | +| Method | Supervised fine-tuning, LoRA (r=16, α=32) on q/k/v/o/gate/up/down | +| Data | 778 meal→items examples (Turkish / English / mixed); 739 train / 39 eval | +| Schedule | 3 epochs, 279 steps, lr 2e-4, batch 4 × grad-accum 2, linear decay | +| Optimizer | AdamW 8-bit, weight decay 0.01 | +| Hardware | Single NVIDIA T4 (~20 min) | +| Export | LoRA merged into 16-bit weights | + +## Evaluation + +Held-out set of **94 meal descriptions** (53 Turkish, 34 English, 7 mixed), with zero +overlap with the training data. Parsing metrics score the model output directly; nutrition +metrics reflect the **full pipeline** (this parser + nutrition table + calculator). + +**Parsing** + +| Metric | Value | +|---|---| +| Item Precision / Recall / F1 | 100% / 100% / 100% | +| Parse failures | 0 / 94 | +| Unresolved foods (table gaps) | 0 | + +**Nutrition (full pipeline)** + +| Metric | Value | +|---|---| +| Calorie MAPE | 3.1% | +| Within ±15% | 85 / 91 | +| Protein / Carbs / Fat MAE | 0.5 g / 1.5 g / 0.4 g | + +**Calorie MAPE by language** + +| Language | MAPE | n | +|---|---|---| +| Turkish | 3.3% | 51 | +| English | 2.7% | 33 | +| Mixed (TR/EN) | 3.4% | 7 | + +## Bias, risks, and limitations + +- **Parsing only.** Calorie/macro accuracy depends on the accompanying nutrition table and + calculator, which are not part of this repository. +- **Portion ambiguity.** Vague amounts (e.g. "1 bowl of rice") are resolved with default + serving sizes; the true amount may differ. This is the dominant source of residual error. +- **Table coverage.** Foods outside the nutrition table cannot be scored downstream; + long-tail coverage is the main lever for production accuracy and is addressed by expanding + the table, not by retraining. +- **JSON robustness.** Output is valid JSON in the large majority of cases, but consuming + applications should still guard against an occasional malformed response (e.g. retry once). + +## Versioning + +Versions are published as git tags on this repository. Pin a specific version in production +with `revision="v1"`. Future improvements are added as new tags (`v2`, `v3`, …) without +breaking pinned consumers. + +## Technical references + +- Qwen2.5 Technical Report — [arXiv:2412.15115](https://arxiv.org/abs/2412.15115) +- LoRA: Low-Rank Adaptation of Large Language Models — [arXiv:2106.09685](https://arxiv.org/abs/2106.09685) +- Unsloth — [github.com/unslothai/unsloth](https://github.com/unslothai/unsloth) + +## Acknowledgements + +Built on [Qwen2.5](https://huggingface.co/Qwen) by the Qwen team, and trained efficiently +with [Unsloth](https://github.com/unslothai/unsloth). + +## License + +Fine-tuned from `Qwen/Qwen2.5-3B-Instruct`; use is subject to the +[Qwen Research License](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct/blob/main/LICENSE) +of the base model. \ No newline at end of file diff --git a/chat_template.jinja b/chat_template.jinja new file mode 100644 index 0000000..bdf7919 --- /dev/null +++ b/chat_template.jinja @@ -0,0 +1,54 @@ +{%- if tools %} + {{- '<|im_start|>system\n' }} + {%- if messages[0]['role'] == 'system' %} + {{- messages[0]['content'] }} + {%- else %} + {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }} + {%- 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 XML tags:\n" }} + {%- for tool in tools %} + {{- "\n" }} + {{- tool | tojson }} + {%- endfor %} + {{- "\n\n\nFor each function call, return a json object with function name and arguments within XML tags:\n\n{\"name\": , \"arguments\": }\n<|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 Qwen, created by Alibaba Cloud. You are a helpful assistant.<|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\n{"name": "' }} + {{- tool_call.name }} + {{- '", "arguments": ' }} + {{- tool_call.arguments | tojson }} + {{- '}\n' }} + {%- endfor %} + {{- '<|im_end|>\n' }} + {%- elif message.role == "tool" %} + {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %} + {{- '<|im_start|>user' }} + {%- endif %} + {{- '\n\n' }} + {{- 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You are a helpful assistant.' }}\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 XML tags:\\n\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n\\n\\nFor each function call, return a json object with function name and arguments within XML tags:\\n\\n{\\\"name\\\": , \\\"arguments\\\": }\\n<|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 Qwen, created by Alibaba Cloud. You are a helpful assistant.<|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\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n' }}\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\\n' }}\n {{- message.content }}\n {{- '\\n' }}\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" +} \ No newline at end of file