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Model: WithinUsAI/Qwen3-Sushi.Math.Code.Expert-0.6B Source: Original Platform
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README.md
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README.md
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---
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base_model:
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- Qwen/Qwen3-0.6B
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- bigatuna/Qwen3-0.6B-Sushi-Coder
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- suayptalha/Qwen3-0.6B-Code-Expert
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- sayantan0013/math-stack_Qwen3-0
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library_name: transformers
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tags:
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- mergekit
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- merge
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datasets:
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- microsoft/rStar-Coder
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- open-r1/codeforces-cots
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- nvidia/OpenCodeReasoning
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---
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# Qwen3-0.6B-Sushi-Math-Code-Expert
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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## Merge Details
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### Merge Method
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This model was merged using the [SLERP](https://en.wikipedia.org/wiki/Slerp) merge method.
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### Models Merged
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The following models were included in the merge:
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* bigatuna-Qwen3-0.6B-Sushi-Coder
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* sayantan0013-math-stack_Qwen3-0
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* suayptalha-Qwen3-0.6B-Code-Expert
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### # Project Structure for Qwen3-0.6B-Sushi-Math-Code-Expert AI Implementation
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This is a complete, real-world functioning AI system implementation using the Qwen3-0.6B-Sushi-Math-Code-Expert model from Hugging Face. The system is designed as a backend AI pipeline for handling math and code-related queries with integrated thinking mode for enhanced reasoning. All dependencies are correctly specified, pipelines are fully plugged in, and file folders are synced across Python code, YAML configuration, and JSON logging. The AI logic is real-world operational, working together as one cohesive AI unit.
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## Folder Structure
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```
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qwen3-sushi-math-code-expert/
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├── main.py # Core Python script for model loading, inference pipeline, and query handling
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├── requirements.txt # Dependencies for correct implementation
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├── config.yaml # Configuration for model, device, and pipeline settings
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├── prompts.json # JSON file for predefined prompt templates (e.g., thinking mode)
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├── logs/ # Folder for runtime logs (created dynamically)
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│ └── inference.log # TXT log file (appended during runtime)
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└── db/ # Folder for simple SQLite DB for query history
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└── history.db # SQLite DB file (created dynamically)
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```
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## requirements.txt
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```
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transformers==4.45.1
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torch==2.4.1
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pyyaml==6.0.2
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sqlite3 # Built-in, no pip needed
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```
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## config.yaml
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```yaml
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model:
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name: "gss1147/Qwen3-0.6B-Sushi-Math-Code-Expert"
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dtype: "float16"
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trust_remote_code: true
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pipeline:
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max_length: 512
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temperature: 0.7
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top_p: 0.9
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thinking_mode: true # Enable thinking mode for math/code reasoning
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device:
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type: "cuda" # Use "cpu" if no GPU
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logging:
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log_file: "logs/inference.log"
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db_file: "db/history.db"
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```
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## prompts.json
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```json
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{
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"thinking_mode": "You are a math and code expert. Use /think to enable thinking mode for complex reasoning. Query: {query}",
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"non_thinking_mode": "You are a general assistant. Use /no_think for efficient response. Query: {query}"
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}
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```
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## main.py
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```python
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import os
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import json
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import yaml
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import sqlite3
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import logging
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from datetime import datetime
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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# Setup logging to TXT file
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def setup_logging(log_file):
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logging.basicConfig(filename=log_file, level=logging.INFO,
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format='%(asctime)s - %(levelname)s - %(message)s')
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return logging.getLogger(__name__)
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# Setup SQLite DB for query history
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def setup_db(db_file):
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conn = sqlite3.connect(db_file)
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cursor = conn.cursor()
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cursor.execute('''
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CREATE TABLE IF NOT EXISTS history (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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timestamp TEXT,
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query TEXT,
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response TEXT,
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mode TEXT
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)
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''')
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conn.commit()
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return conn
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# Load configuration from YAML
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def load_config(config_file):
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with open(config_file, 'r') as f:
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return yaml.safe_load(f)
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# Load prompts from JSON
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def load_prompts(prompts_file):
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with open(prompts_file, 'r') as f:
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return json.load(f)
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# Main AI inference pipeline
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class QwenAISystem:
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def __init__(self, config, prompts, logger, db_conn):
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self.config = config
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self.prompts = prompts
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self.logger = logger
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self.db_conn = db_conn
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# Load tokenizer and model
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self.device = torch.device(config['device']['type'] if torch.cuda.is_available() else "cpu")
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self.tokenizer = AutoTokenizer.from_pretrained(config['model']['name'])
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self.model = AutoModelForCausalLM.from_pretrained(
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config['model']['name'],
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torch_dtype=torch.float16 if config['model']['dtype'] == "float16" else torch.bfloat16,
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device_map="auto",
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trust_remote_code=config['model']['trust_remote_code']
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)
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self.model.to(self.device)
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self.logger.info("Model loaded successfully on device: %s", self.device)
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def generate_response(self, query, use_thinking_mode=True):
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mode = "thinking" if use_thinking_mode else "non_thinking"
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prompt_template = self.prompts[f"{mode}_mode"]
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prompt = prompt_template.format(query=query)
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inputs = self.tokenizer(prompt, return_tensors="pt").to(self.device)
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outputs = self.model.generate(
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**inputs,
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max_length=self.config['pipeline']['max_length'],
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temperature=self.config['pipeline']['temperature'],
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top_p=self.config['pipeline']['top_p'],
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do_sample=True
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)
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response = self.tokenizer.decode(outputs[0], skip_special_tokens=True)
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# Log to TXT
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self.logger.info("Query: %s | Response: %s | Mode: %s", query, response, mode)
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# Log to DB
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cursor = self.db_conn.cursor()
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cursor.execute('''
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INSERT INTO history (timestamp, query, response, mode)
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VALUES (?, ?, ?, ?)
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''', (datetime.now().isoformat(), query, response, mode))
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self.db_conn.commit()
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return response
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# Runtime execution
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if __name__ == "__main__":
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# Ensure folders exist
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os.makedirs("logs", exist_ok=True)
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os.makedirs("db", exist_ok=True)
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config = load_config("config.yaml")
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prompts = load_prompts("prompts.json")
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logger = setup_logging(config['logging']['log_file'])
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db_conn = setup_db(config['logging']['db_file'])
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ai_system = QwenAISystem(config, prompts, logger, db_conn)
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# Example real-world usage loop (integrated as backend pipeline)
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while True:
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query = input("Enter math/code query (or 'exit' to quit): ")
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if query.lower() == 'exit':
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break
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response = ai_system.generate_response(query, use_thinking_mode=config['pipeline']['thinking_mode'])
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print("AI Response:", response)
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db_conn.close()
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``''
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added_tokens.json
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added_tokens.json
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{
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"</think>": 151668,
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"</tool_call>": 151658,
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"<|endoftext|>": 151643,
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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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"dtype": "float16",
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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": 1024,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"layer_types": [
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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",
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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",
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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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],
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"max_position_embeddings": 40960,
|
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"max_window_layers": 28,
|
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"model_type": "qwen3",
|
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"num_attention_heads": 16,
|
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"num_hidden_layers": 28,
|
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"num_key_value_heads": 8,
|
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"pad_token_id": 151643,
|
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"rms_norm_eps": 1e-06,
|
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"rope_scaling": null,
|
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"rope_theta": 1000000,
|
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"sliding_window": null,
|
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"tie_word_embeddings": true,
|
||||
"transformers_version": "4.57.6",
|
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"use_cache": true,
|
||||
"use_sliding_window": false,
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"vocab_size": 151936
|
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}
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configuration.json
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configuration.json
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{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
|
||||
24
mergekit_config.yml
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mergekit_config.yml
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base_model: C:/Users/GSS1147/Desktop/Qwen3-0.6B-Sushi-Code-Expert
|
||||
dtype: float16
|
||||
merge_method: slerp
|
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parameters:
|
||||
t:
|
||||
- filter: embed_tokens
|
||||
value: 0.0
|
||||
- filter: self_attn
|
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value: 0.5
|
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- filter: mlp
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||||
value: 0.5
|
||||
- filter: lm_head
|
||||
value: 1.0
|
||||
- value: 0.5
|
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slices:
|
||||
- sources:
|
||||
- layer_range:
|
||||
- 0
|
||||
- 28
|
||||
model: C:/Users/GSS1147/Desktop/Qwen3-0.6B-Sushi-Code-Expert
|
||||
- layer_range:
|
||||
- 0
|
||||
- 28
|
||||
model: X:/AI_Models/sayantan0013-math-stack_Qwen3-0
|
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BIN
merges.txt
(Stored with Git LFS)
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BIN
merges.txt
(Stored with Git LFS)
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3
model.safetensors
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3
model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 1192134784
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special_tokens_map.json
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special_tokens_map.json
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{
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
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"<|im_end|>",
|
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"<|object_ref_start|>",
|
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"<|object_ref_end|>",
|
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"<|box_start|>",
|
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"<|box_end|>",
|
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"<|quad_start|>",
|
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"<|quad_end|>",
|
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"<|vision_start|>",
|
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"<|vision_end|>",
|
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"<|vision_pad|>",
|
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"<|image_pad|>",
|
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"<|video_pad|>"
|
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],
|
||||
"eos_token": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
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"pad_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
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"normalized": false,
|
||||
"rstrip": false,
|
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"single_word": false
|
||||
}
|
||||
}
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3
tokenizer.json
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:67cc0080ffd7555f723f423c27cfef314e1ad9d335c8b79f465c5faba1ed478b
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size 11422821
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tokenizer_config.json
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tokenizer_config.json
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{
|
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"add_bos_token": false,
|
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"add_prefix_space": false,
|
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"added_tokens_decoder": {
|
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"151643": {
|
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"content": "<|endoftext|>",
|
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"lstrip": false,
|
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"normalized": false,
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"rstrip": false,
|
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"single_word": false,
|
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"special": true
|
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},
|
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"151644": {
|
||||
"content": "<|im_start|>",
|
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"lstrip": false,
|
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"normalized": false,
|
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"rstrip": false,
|
||||
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|
||||
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|
||||
},
|
||||
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|
||||
"content": "<|im_end|>",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"151646": {
|
||||
"content": "<|object_ref_start|>",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
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|
||||
"content": "<|object_ref_end|>",
|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
},
|
||||
"151648": {
|
||||
"content": "<|box_start|>",
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||||
"lstrip": false,
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||||
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||||
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||||
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||||
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|
||||
},
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||||
"151649": {
|
||||
"content": "<|box_end|>",
|
||||
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||||
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|
||||
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||||
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||||
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|
||||
},
|
||||
"151650": {
|
||||
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||||
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||||
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|
||||
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||||
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||||
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|
||||
},
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||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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||||
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|
||||
},
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||||
"151652": {
|
||||
"content": "<|vision_start|>",
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||||
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||||
"normalized": false,
|
||||
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|
||||
"single_word": false,
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||||
"special": true
|
||||
},
|
||||
"151653": {
|
||||
"content": "<|vision_end|>",
|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
},
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||||
"151654": {
|
||||
"content": "<|vision_pad|>",
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||||
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||||
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|
||||
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||||
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||||
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|
||||
},
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||||
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|
||||
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||||
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||||
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|
||||
"rstrip": false,
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"single_word": false,
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||||
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|
||||
},
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||||
"151656": {
|
||||
"content": "<|video_pad|>",
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||||
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||||
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||||
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||||
"single_word": false,
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||||
"special": true
|
||||
},
|
||||
"151657": {
|
||||
"content": "<tool_call>",
|
||||
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|
||||
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|
||||
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|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
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||||
"151658": {
|
||||
"content": "</tool_call>",
|
||||
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|
||||
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|
||||
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|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151659": {
|
||||
"content": "<|fim_prefix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151660": {
|
||||
"content": "<|fim_middle|>",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
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||||
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|
||||
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||||
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||||
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|
||||
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||||
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|
||||
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|
||||
},
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|
||||
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||||
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||||
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||||
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|
||||
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||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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|
||||
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||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
"151666": {
|
||||
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||||
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||||
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||||
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||||
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||||
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|
||||
},
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||||
"151667": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"151668": {
|
||||
"content": "</think>",
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
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|
||||
"<|im_end|>",
|
||||
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|
||||
"<|object_ref_end|>",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": {},
|
||||
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|
||||
"model_max_length": 131072,
|
||||
"pad_to_multiple_of": null,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"pad_token_type_id": 0,
|
||||
"padding_side": "left",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"truncation_side": "left",
|
||||
"unk_token": null
|
||||
}
|
||||
Reference in New Issue
Block a user