Copy from nickoo004/queryshield-1.5b - community contribution

README.md

@@ -0,0 +1,227 @@
+---
+license: mit
+base_model: Qwen/Qwen2.5-1.5B-Instruct
+language:
+  - en
+  - uz
+  - ru
+  - kk
+  - kaa
+tags:
+  - queryshield
+  - prompt-optimization
+  - multilingual
+  - instruction-tuning
+  - lora
+  - qlora
+  - qwen2.5
+  - uzbek
+  - karakalpak
+  - kazakh
+  - central-asia
+  - fine-tuned
+pipeline_tag: text-generation
+datasets:
+- nickoo004/queryshield-multilingual
+---
+
+# QueryShield — Multilingual Prompt Optimizer
+
+**QueryShield-1.5B** is a fine-tuned version of [Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct) trained to rewrite raw, messy user queries into detailed, structured instruction prompts for downstream LLMs — across 5 languages and 30 professional domains.
+
+> Given a raw user question → outputs an expert-level optimized prompt telling a downstream LLM *how* to answer it.
+
+---
+
+## What it does
+
+Most LLMs perform significantly better when given structured, detailed prompts rather than raw user input. QueryShield sits **between the user and the LLM** — it takes the raw query and rewrites it into a high-quality instruction prompt automatically.
+
+```
+User: "menga diabetni boshqarish uchun ovqat rejimi ayting"
+         ↓  QueryShield
+Optimized: "As a Medical Expert, the user is asking in Uzbek about dietary
+            management for diabetes with high blood sugar. Provide a structured
+            3-tier response covering: diabetes basics, dietary assessment, and
+            an actionable meal plan. Respond entirely in Uzbek. Avoid jargon..."
+         ↓  Downstream LLM
+Final answer in Uzbek ✅
+```
+
+---
+
+## Model Details
+
+| Property | Value |
+|---|---|
+| **Base model** | Qwen/Qwen2.5-1.5B-Instruct |
+| **Training data** | [QueryShield Multilingual Dataset](https://huggingface.co/datasets/nickoo004/queryshield-multilingual) |
+| **Training rows** | 19,530 |
+| **Epochs** | 3 |
+| **Train loss** | 0.88 → 0.47 |
+| **Eval loss** | 0.967 (best checkpoint) |
+| **GPU** | NVIDIA RTX 3090 24GB |
+| **Training time** | ~3.7 hours |
+| **Parameters** | 1.5B total / 147M trainable (8.7%) |
+| **Live demo** | [▶ Kaggle Notebook](https://www.kaggle.com/code/nursultankoshekbaev/queryshield-1-5b) |
+
+---
+
+## Languages
+
+| Language | Code | Support |
+|---|---|---|
+| English | `en` | ✅ Full |
+| Uzbek | `uz` | ✅ Full |
+| Russian | `ru` | ✅ Full |
+| Kazakh | `kk` | ✅ Full |
+| Karakalpak | `kaa` | ✅ Good |
+
+**Cross-lingual** scenarios supported — user can write in one language and request output in another (e.g., Uzbek input → Russian output).
+
+---
+
+## Quick Start
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model_id = "nickoo004/queryshield-1.5b"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+    trust_remote_code=True,
+)
+
+SYSTEM = (
+    "You are QueryShield, a multilingual prompt optimizer. "
+    "Given a raw user question, rewrite it into a detailed instruction "
+    "prompt for a downstream LLM expert. "
+    "User language: {in_lang}. Response language: {out_lang}. "
+    "Expert role: {role}."
+)
+
+def optimize_prompt(user_question, input_language, output_language, role):
+    messages = [
+        {"role": "system", "content": SYSTEM.format(
+            in_lang=input_language,
+            out_lang=output_language,
+            role=role,
+        )},
+        {"role": "user", "content": user_question},
+    ]
+    text = tokenizer.apply_chat_template(
+        messages, tokenize=False, add_generation_prompt=True
+    )
+    inputs = tokenizer(text, return_tensors="pt").to(model.device)
+    with torch.no_grad():
+        output = model.generate(
+            **inputs,
+            max_new_tokens=512,
+            temperature=0.7,
+            do_sample=True,
+            repetition_penalty=1.1,
+            pad_token_id=tokenizer.eos_token_id,
+        )
+    new_tokens = output[0][inputs["input_ids"].shape[1]:]
+    return tokenizer.decode(new_tokens, skip_special_tokens=True)
+
+
+# Example 1 — Uzbek monolingual
+result = optimize_prompt(
+    user_question="menga diabetni boshqarish uchun eng yaxshi ovqatlanish rejimini ayting",
+    input_language="Uzbek",
+    output_language="Uzbek",
+    role="Medical Expert",
+)
+print(result)
+
+# Example 2 — Cross-lingual: Kazakh -> Uzbek
+result = optimize_prompt(
+    user_question="менің фермамда топырақ сапасы нашар, не істеуім керек?",
+    input_language="Kazakh",
+    output_language="Uzbek",
+    role="Agricultural Scientist",
+)
+print(result)
+```
+
+---
+
+## Live Demo
+
+**[▶ Run on Kaggle](https://www.kaggle.com/code/nursultankoshekbaev/queryshield-1-5b)** — no setup needed, free GPU included.
+
+Tests all 7 cases: English, Uzbek, Russian, Kazakh, Karakalpak + 2 cross-lingual pairs.
+
+---
+
+## Supported Domains (30 total)
+
+| Domain | Expert Role |
+|---|---|
+| Software Engineering | Senior Software Engineer |
+| Healthcare & Medicine | Medical Expert |
+| Finance & Banking | Financial Analyst |
+| Legal & Law | Legal Advisor |
+| Data Science & AI | Data Scientist |
+| Cybersecurity | Cybersecurity Specialist |
+| Aviation & Aerospace | Aerospace Engineer |
+| Agriculture | Agricultural Scientist |
+| Education & Teaching | Experienced Educator |
+| Automotive | Automotive Engineer |
+| Pharmaceuticals | Pharmaceutical Researcher |
+| Manufacturing | Manufacturing Expert |
+| Civil / Mechanical / Electrical Engineering | Domain Engineer |
+| Business & Marketing | Business Strategist |
+| Creative Writing | Professional Writer |
+| … and 15 more | … |
+
+---
+
+## Training Details
+
+### Dataset
+- **Source:** [nickoo004/queryshield-multilingual](https://huggingface.co/datasets/nickoo004/queryshield-multilingual)
+- **19,530 rows** across 5 languages and 30 domains
+- Generated by DeepSeek, Gemini, and Qwen2.5-14B
+
+### Loss Curve
+```
+Epoch 1.0  ->  train: 1.023  |  eval: 0.997
+Epoch 2.5  ->  train: 0.731  |  eval: 0.967  <- best checkpoint
+```
+
+---
+
+## Limitations
+
+- Karakalpak support is functional but may be less consistent than other languages due to limited training data for this low-resource language
+- `optimized_prompt` output is always structured as an English instruction — this is by design
+- Best results on domains covered in training data; novel domains may produce generic prompts
+- Not suitable for harmful, illegal, or unethical query optimization
+
+---
+
+## Citation
+
+```bibtex
+@model{queryshield_1_5b_2026,
+  author    = {nickoo004},
+  title     = {QueryShield-1.5B: Multilingual Prompt Optimizer},
+  year      = {2026},
+  publisher = {Hugging Face},
+  url       = {https://huggingface.co/nickoo004/queryshield-1.5b}
+}
+```
+
+---
+
+## License
+
+This model is released under the **MIT License**.
+Base model license: [Qwen License](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct/blob/main/LICENSE)

added_tokens.json

@@ -0,0 +1,24 @@
+{
+  "</tool_call>": 151658,
+  "<tool_call>": 151657,
+  "<|box_end|>": 151649,
+  "<|box_start|>": 151648,
+  "<|endoftext|>": 151643,
+  "<|file_sep|>": 151664,
+  "<|fim_middle|>": 151660,
+  "<|fim_pad|>": 151662,
+  "<|fim_prefix|>": 151659,
+  "<|fim_suffix|>": 151661,
+  "<|im_end|>": 151645,
+  "<|im_start|>": 151644,
+  "<|image_pad|>": 151655,
+  "<|object_ref_end|>": 151647,
+  "<|object_ref_start|>": 151646,
+  "<|quad_end|>": 151651,
+  "<|quad_start|>": 151650,
+  "<|repo_name|>": 151663,
+  "<|video_pad|>": 151656,
+  "<|vision_end|>": 151653,
+  "<|vision_pad|>": 151654,
+  "<|vision_start|>": 151652
+}

config.json

@@ -0,0 +1,28 @@
+{
+  "_name_or_path": "Qwen/Qwen2.5-1.5B-Instruct",
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "eos_token_id": 151645,
+  "hidden_act": "silu",
+  "hidden_size": 1536,
+  "initializer_range": 0.02,
+  "intermediate_size": 8960,
+  "max_position_embeddings": 32768,
+  "max_window_layers": 21,
+  "model_type": "qwen2",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 2,
+  "rms_norm_eps": 1e-06,
+  "rope_theta": 1000000.0,
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.44.0",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}

generation_config.json

@@ -0,0 +1,14 @@
+{
+  "bos_token_id": 151643,
+  "do_sample": true,
+  "eos_token_id": [
+    151645,
+    151643
+  ],
+  "pad_token_id": 151643,
+  "repetition_penalty": 1.1,
+  "temperature": 0.7,
+  "top_k": 20,
+  "top_p": 0.8,
+  "transformers_version": "4.44.0"
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8ceaa4ad40008d0a0abced47568e80e9403e1250819357e6024f70cfeacba914
+size 3087467144

special_tokens_map.json

@@ -0,0 +1,31 @@
+{
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "eos_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

@@ -0,0 +1,208 @@
+{
+  "add_bos_token": false,
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151645": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151646": {
+      "content": "<|object_ref_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151647": {
+      "content": "<|object_ref_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151648": {
+      "content": "<|box_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151649": {
+      "content": "<|box_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151650": {
+      "content": "<|quad_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151651": {
+      "content": "<|quad_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151652": {
+      "content": "<|vision_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151653": {
+      "content": "<|vision_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151654": {
+      "content": "<|vision_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151655": {
+      "content": "<|image_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151656": {
+      "content": "<|video_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151657": {
+      "content": "<tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151658": {
+      "content": "</tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151659": {
+      "content": "<|fim_prefix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151660": {
+      "content": "<|fim_middle|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151661": {
+      "content": "<|fim_suffix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151662": {
+      "content": "<|fim_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151663": {
+      "content": "<|repo_name|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151664": {
+      "content": "<|file_sep|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "bos_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 Qwen, created by Alibaba Cloud. 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 <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 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<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",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "model_max_length": 131072,
+  "pad_token": "<|im_end|>",
+  "padding_side": "right",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}