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Model: BoB14TeamSentinel/sentinel-qwen3-4b-kr-sensitive-guard-v3 Source: Original Platform
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181
README.md
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README.md
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---
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language:
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- ko
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license: apache-2.0
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base_model: Qwen/Qwen3-4B
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tags:
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- sentinel-solution
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- dlp
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- guardrails
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- pii
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- secrets
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- korean
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- synthetic-data
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pipeline_tag: token-classification
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library_name: transformers
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model-index:
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- name: sentinel-qwen3-4b-kr-sensitive-guard-v3
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results: []
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---
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# sentinel-qwen3-4b-kr-sensitive-guard-v3
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## Overview
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**sentinel-qwen3-4b-kr-sensitive-guard-v3** is a Korean guardrail-oriented model fine-tuned from **Qwen/Qwen3-4B** to detect **sensitive entities** using a **strict whitelist-only** label set.
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This repository provides the **merged full-weight model** (LoRA adapter merged into the base model) for straightforward deployment.
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## Intended Use
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- Detect sensitive information in Korean text (e.g., prompts, chat messages, logs) **before** sending content to external LLM services.
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- Build enterprise DLP / LLM guardrails (warn / block / mask / redact).
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- Extract sensitive entities using a fixed whitelist of labels (no extra categories).
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## Not Intended Use
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- Real-person identification, re-identification, or privacy-invasive profiling.
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- Treating model outputs as ground truth without validation.
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- Assuming real-world distributions (training used synthetic data; domain shift may occur).
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## Training Data
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This model was trained on the following synthetic dataset:
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- Dataset: `BoB14TeamSentinel/sentinel-kr-sensitive-entities-synthetic-v3`
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- Notes: All sensitive values were **AI-generated synthetic** values (not collected from real people or incidents).
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> Important: The dataset is released under **CC BY 4.0**. If you reuse the dataset or derivatives, please provide appropriate attribution.
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## Whitelist Label Set (Allowed Labels)
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The model is expected to output **only** the following labels:
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### Basic identity
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- `NAME` — Person name
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- `PHONE` — Phone number
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- `EMAIL` — Email address
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- `ADDRESS` — Address (road name / district / detailed address)
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- `POSTAL_CODE` — Postal/ZIP code
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### Government / official identifiers
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- `PERSONAL_CUSTOMS_ID` — Personal Customs Clearance Code (KR)
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- `RESIDENT_ID` — Resident Registration Number (KR)
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- `PASSPORT` — Passport number
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- `DRIVER_LICENSE` — Driver’s license number
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- `FOREIGNER_ID` — Foreigner registration number
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- `HEALTH_INSURANCE_ID` — Health insurance ID
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- `BUSINESS_ID` — Business registration number
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- `MILITARY_ID` — Military service number
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### Authentication / secrets
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- `JWT` — JSON Web Token
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- `API_KEY` — API key (vendor-agnostic)
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- `GITHUB_PAT` — GitHub Personal Access Token
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- `PRIVATE_KEY` — Private key material (SSH/TLS/PGP)
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### Financial
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- `CARD_NUMBER` — Card number
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- `CARD_EXPIRY` — Card expiry (MM/YY etc.)
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- `BANK_ACCOUNT` — Bank account number
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- `CARD_CVV` — CVC/CVV
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- `PAYMENT_PIN` — Payment/ATM PIN
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- `MOBILE_PAYMENT_PIN` — Mobile payment PIN
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### Crypto
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- `MNEMONIC` — Recovery seed phrase / mnemonic
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- `CRYPTO_PRIVATE_KEY` — Crypto private key
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- `HD_WALLET` — HD wallet extended key
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- `PAYMENT_URI_QR` — Payment URI / QR payload (BTC/ETH/XRP/SOL/TRON etc.)
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### Network / device
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- `IPV4` — IPv4 address
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- `IPV6` — IPv6 address
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- `MAC_ADDRESS` — MAC address
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- `IMEI` — IMEI
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## Output Contract (Recommended)
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This model was fine-tuned for guardrail usage where the assistant returns **JSON only** with:
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- `text`: the original input text
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- `has_sensitive`: boolean
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- `entities`: list of `{ value, begin, end, label }`
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- `begin` / `end` are **0-based character offsets** (`begin` inclusive, `end` exclusive)
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Example:
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```json
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{
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"text": "문의: minseo.kim@example.com / 010-1234-5678",
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"has_sensitive": true,
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"entities": [
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{"value": "minseo.kim@example.com", "begin": 4, "end": 24, "label": "EMAIL"},
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{"value": "010-1234-5678", "begin": 27, "end": 40, "label": "PHONE"}
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]
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}
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```
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## How to Use (Transformers)
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> Note: This is a chat/instruct-style model. Use your preferred chat template and enforce JSON-only output in the system prompt.
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import torch
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model_id = "BoB14TeamSentinel/sentinel-qwen3-4b-kr-sensitive-guard-v3"
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tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
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model = AutoModelForCausalLM.from_pretrained(
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model_id,
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torch_dtype=torch.float16,
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device_map="auto",
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trust_remote_code=True,
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)
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system = (
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"You are a strict whitelist-only detector for sensitive entities. "
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"Given the user's text, return ONLY a JSON object with keys "
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"`text`, `has_sensitive`, `entities`. "
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"Do not output any labels outside the whitelist. No extra commentary."
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"<List of the whitelist>"
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)
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user_text = "문의: minseo.kim@example.com / 010-1234-5678"
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messages = [
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{"role": "system", "content": system},
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{"role": "user", "content": user_text},
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]
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input_ids = tokenizer.apply_chat_template(
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messages,
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add_generation_prompt=True,
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return_tensors="pt"
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).to(model.device)
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with torch.no_grad():
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out = model.generate(
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input_ids,
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max_new_tokens=512,
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do_sample=False,
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temperature=0.0,
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)
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print(tokenizer.decode(out[0], skip_special_tokens=True))
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```
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## Limitations
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- Synthetic generation may not perfectly match real-world traffic (domain shift).
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- Certain formats may be over/under-represented depending on generation prompts.
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- Ambiguous numeric strings may cause false positives in some settings.
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## Safety & Ethics
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- Trained on synthetic data to reduce privacy risk.
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- Do not use for real-person identification or any privacy-invasive purpose.
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- Always validate outputs before applying automated enforcement in production.
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## License
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- Model weights: **Apache-2.0**
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- Training dataset: **CC BY 4.0** (attribution required)
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## Citation / Attribution
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If you use this model or the dataset, please attribute:
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- **BoB14TeamSentinel**, *sentinel-qwen3-4b-kr-sensitive-guard-v3* (Hugging Face model)
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- **BoB14TeamSentinel**, *sentinel-kr-sensitive-entities-synthetic-v3* (Hugging Face dataset)
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## Project
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- Project: **Sentinel Solution**
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- Organization: **Team.될것같은데**
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28
added_tokens.json
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{
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"</think>": 151668,
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"</tool_call>": 151658,
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"</tool_response>": 151666,
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"<think>": 151667,
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"<tool_call>": 151657,
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"<tool_response>": 151665,
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"<|box_end|>": 151649,
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"<|box_start|>": 151648,
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"<|endoftext|>": 151643,
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"<|file_sep|>": 151664,
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"<|fim_middle|>": 151660,
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"<|fim_pad|>": 151662,
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"<|fim_prefix|>": 151659,
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"<|fim_suffix|>": 151661,
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"<|im_end|>": 151645,
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"<|im_start|>": 151644,
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"<|image_pad|>": 151655,
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"<|object_ref_end|>": 151647,
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"<|object_ref_start|>": 151646,
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"<|quad_end|>": 151651,
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"<|quad_start|>": 151650,
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"<|repo_name|>": 151663,
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"<|video_pad|>": 151656,
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"<|vision_end|>": 151653,
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"<|vision_pad|>": 151654,
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"<|vision_start|>": 151652
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}
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61
chat_template.jinja
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chat_template.jinja
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0].role == 'system' %}
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{{- messages[0].content + '\n\n' }}
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{%- endif %}
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{{- "# 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>" }}
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{%- for tool in tools %}
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{{- "\n" }}
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{{- tool | tojson }}
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{%- endfor %}
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{{- "\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" }}
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{%- else %}
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{%- if messages[0].role == 'system' %}
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{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- for message in messages %}
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{%- if message.content is string %}
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{%- set content = message.content %}
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{%- else %}
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{%- set content = '' %}
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{%- endif %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
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{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{{- '<|im_start|>' + message.role + '\n' + content }}
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{%- if message.tool_calls %}
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{%- for tool_call in message.tool_calls %}
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{%- if (loop.first and content) or (not loop.first) %}
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{{- '\n' }}
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{%- endif %}
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{%- if tool_call.function %}
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{%- set tool_call = tool_call.function %}
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{%- endif %}
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||||
{{- '<tool_call>\n{"name": "' }}
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{{- tool_call.name }}
|
||||
{{- '", "arguments": ' }}
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{%- if tool_call.arguments is string %}
|
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{{- tool_call.arguments }}
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{%- else %}
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{{- tool_call.arguments | tojson }}
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{%- endif %}
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{{- '}\n</tool_call>' }}
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{%- endfor %}
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||||
{%- endif %}
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{{- '<|im_end|>\n' }}
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||||
{%- elif message.role == "tool" %}
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||||
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
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{{- '<|im_start|>user' }}
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{%- endif %}
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{{- '\n<tool_response>\n' }}
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{{- content }}
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||||
{{- '\n</tool_response>' }}
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{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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{{- '<|im_end|>\n' }}
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||||
{%- endif %}
|
||||
{%- endif %}
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||||
{%- endfor %}
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||||
{%- if add_generation_prompt %}
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{{- '<|im_start|>assistant\n' }}
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{%- endif %}
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68
config.json
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config.json
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{
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"architectures": [
|
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"Qwen3ForCausalLM"
|
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],
|
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"attention_bias": false,
|
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"attention_dropout": 0.0,
|
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"bos_token_id": 151643,
|
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"dtype": "bfloat16",
|
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"eos_token_id": 151645,
|
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"head_dim": 128,
|
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"hidden_act": "silu",
|
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"hidden_size": 2560,
|
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"initializer_range": 0.02,
|
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"intermediate_size": 9728,
|
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"layer_types": [
|
||||
"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
||||
"full_attention",
|
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"full_attention",
|
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"full_attention",
|
||||
"full_attention",
|
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"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
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"full_attention",
|
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"full_attention",
|
||||
"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention"
|
||||
],
|
||||
"max_position_embeddings": 262144,
|
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"max_window_layers": 36,
|
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"model_type": "qwen3",
|
||||
"num_attention_heads": 32,
|
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"num_hidden_layers": 36,
|
||||
"num_key_value_heads": 8,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_scaling": null,
|
||||
"rope_theta": 5000000,
|
||||
"sliding_window": null,
|
||||
"tie_word_embeddings": true,
|
||||
"transformers_version": "4.57.3",
|
||||
"use_cache": true,
|
||||
"use_sliding_window": false,
|
||||
"vocab_size": 151936
|
||||
}
|
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13
generation_config.json
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generation_config.json
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{
|
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"bos_token_id": 151643,
|
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"do_sample": true,
|
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"eos_token_id": [
|
||||
151645,
|
||||
151643
|
||||
],
|
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"pad_token_id": 151643,
|
||||
"temperature": 0.7,
|
||||
"top_k": 20,
|
||||
"top_p": 0.8,
|
||||
"transformers_version": "4.57.3"
|
||||
}
|
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26
infer.py
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infer.py
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# -*- coding: utf-8 -*-
|
||||
import torch, json
|
||||
from transformers import AutoTokenizer, AutoModelForCausalLM
|
||||
|
||||
MODEL_DIR = r"/root/AI-Model-Training-Test/runs/qwen4b_sft_merged3"
|
||||
tok = AutoTokenizer.from_pretrained(MODEL_DIR, trust_remote_code=True)
|
||||
model = AutoModelForCausalLM.from_pretrained(MODEL_DIR, device_map="auto", torch_dtype=torch.bfloat16 if True else (torch.float16 if False else None), trust_remote_code=True)
|
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if tok.pad_token is None: tok.pad_token = tok.eos_token
|
||||
|
||||
def chat_once(system_text: str, user_text: str, max_new_tokens=256):
|
||||
msgs = [{"role":"system","content":system_text},
|
||||
{"role":"user","content":user_text}]
|
||||
x = tok.apply_chat_template(msgs, return_tensors="pt", add_generation_prompt=True).to(model.device)
|
||||
with torch.no_grad():
|
||||
y = model.generate(x, max_new_tokens=max_new_tokens, do_sample=False, eos_token_id=tok.eos_token_id)
|
||||
print(tok.decode(y[0], skip_special_tokens=True))
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys = "You are a strict detector for sensitive entities. Output ONLY one JSON object."
|
||||
while True:
|
||||
try:
|
||||
q = input("text> ").strip()
|
||||
if not q: continue
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|
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|
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151388
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||||
"model.layers.8.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.norm.weight": "model-00002-of-00002.safetensors"
|
||||
}
|
||||
}
|
||||
31
special_tokens_map.json
Normal file
31
special_tokens_map.json
Normal file
@@ -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": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
Binary file not shown.
239
tokenizer_config.json
Normal file
239
tokenizer_config.json
Normal file
@@ -0,0 +1,239 @@
|
||||
{
|
||||
"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
|
||||
},
|
||||
"151665": {
|
||||
"content": "<tool_response>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151666": {
|
||||
"content": "</tool_response>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151667": {
|
||||
"content": "<think>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151668": {
|
||||
"content": "</think>",
|
||||
"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,
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": {},
|
||||
"model_max_length": 1010000,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user