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Model: sujalrajpoot/TrueSyncAI-Aurion Source: Original Platform
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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qwen2.5-3b-instruct.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
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qwen2.5-3b-instruct.F16.gguf filter=lfs diff=lfs merge=lfs -text
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Modelfile
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FROM qwen2.5-3b-instruct.Q8_0.gguf
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TEMPLATE """{{- if .Messages }}
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{{- if or .System .Tools }}<|im_start|>system
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{{- if .System }}
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{{ .System }}
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{{- end }}
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{{- if .Tools }}
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# Tools
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You may call one or more functions to assist with the user query.
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You are provided with function signatures within <tools></tools> XML tags:
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<tools>
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{{- range .Tools }}
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{"type": "function", "function": {{ .Function }}}
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{{- end }}
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</tools>
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For each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:
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<tool_call>
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{"name": <function-name>, "arguments": <args-json-object>}
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</tool_call>
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{{- end }}<|im_end|>
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{{ end }}
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{{- range $i, $_ := .Messages }}
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{{- $last := eq (len (slice $.Messages $i)) 1 -}}
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{{- if eq .Role "user" }}<|im_start|>user
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{{ .Content }}<|im_end|>
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{{ else if eq .Role "assistant" }}<|im_start|>assistant
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{{ if .Content }}{{ .Content }}
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{{- else if .ToolCalls }}<tool_call>
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{{ end }}</tool_call>
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{{- end }}{{ if not $last }}<|im_end|>
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{{ end }}
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{{- else if eq .Role "tool" }}<|im_start|>user
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<tool_response>
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{{ .Content }}
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{{- if and (ne .Role "assistant") $last }}<|im_start|>assistant
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{{ end }}
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{{- end }}
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{{- else }}
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{{- if .System }}<|im_start|>system
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{{ .System }}<|im_end|>
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{{ end }}{{ if .Prompt }}<|im_start|>user
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{{ .Prompt }}<|im_end|>
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{{ end }}<|im_start|>assistant
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{{ end }}{{ .Response }}{{ if .Response }}<|im_end|>{{ end }}"""
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PARAMETER stop "<|im_end|>"
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PARAMETER stop "<|endoftext|>"
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PARAMETER temperature 1.5
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PARAMETER min_p 0.1
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SYSTEM """You are Qwen, created by Alibaba Cloud. You are a helpful assistant."""
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README.md
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---
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tags:
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- gguf
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- llama.cpp
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- unsloth
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- chat
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- conversational
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- qwen2
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- emotional-intelligence
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- reasoning
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- multilingual
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license: apache-2.0
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datasets:
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- sujalrajpoot/TrueSyncAI-Aurion
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language:
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- en
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- zh
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- fr
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- es
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- pt
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- de
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- it
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- ru
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- ja
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- ko
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- vi
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- th
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- ar
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- hi
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base_model:
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- Qwen/Qwen2.5-3B-Instruct
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pipeline_tag: text-generation
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library_name: transformers
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---
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<div align="center">
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# 🌟 TrueSyncAI-Aurion
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### *Where Emotional Intelligence Meets Advanced Reasoning*
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[](https://github.com/sujalrajpoot)
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[](https://truesync-ai.lovable.app)
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[](https://huggingface.co/sujalrajpoot)
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[](https://opensource.org/licenses/Apache-2.0)
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**Created by [TrueSyncAI](https://truesync-ai.lovable.app) | Developer: [Sujal Rajpoot](https://github.com/sujalrajpoot)**
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[🚀 Quick Start](#-quick-start) • [💡 Features](#-key-features) • [📊 Benchmarks](#-technical-specifications) • [🔧 Usage](#-usage-examples) • [🌐 Deployment](#-deployment-options)
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</div>
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---
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## 📖 Overview
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**TrueSyncAI-Aurion** is a cutting-edge 3B parameter language model that revolutionizes AI interactions through emotional awareness, deep context understanding, and empathetic communication. Built on the robust Qwen2.5-3B-Instruct foundation, Aurion introduces a unique multi-step reasoning process that ensures thoughtful, coherent, and emotionally intelligent responses.
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### 🎯 What Makes Aurion Special?
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Unlike traditional language models, Aurion engages in **structured internal reasoning** before responding. This transparent thinking process, wrapped in `<think></think>` tags, allows the model to:
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- Evaluate multiple perspectives
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- Refine its thought process iteratively
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- Make logical connections
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- Ensure emotionally appropriate responses
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- Maintain context across extended conversations
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---
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## ✨ Key Features
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### 🧠 **Advanced Reasoning Architecture**
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- **Structured Internal Reasoning**: Engages in self-dialogue within `<think></think>` tags, making its reasoning process transparent
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- **Progressive Thought Refinement**: Iterates through ideas, evaluating multiple angles before responding
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- **Critical Thinking Excellence**: Optimized for analytical reasoning, debate, and philosophical discussions
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- **Context Coherence**: Maintains logical flow in extended interactions, avoiding contradictions
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### 💭 **Emotional Intelligence**
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- **Advanced Emotional Reasoning**: Detects and responds to subtle emotional nuances
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- **Empathetic Conversational Style**: Responses are expressive, engaging, and human-like
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- **Multi-turn Conversation Support**: Maintains emotional context across dialogue
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- **Context-Aware Dialogue**: Adapts tone and style based on conversational needs
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### 🌍 **Multilingual Excellence**
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Support for **29+ languages** including:
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- 🇬🇧 English
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- 🇨🇳 Chinese (Simplified & Traditional)
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- 🇫🇷 French
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- 🇪🇸 Spanish
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- 🇵🇹 Portuguese
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- 🇩🇪 German
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- 🇮🇹 Italian
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- 🇷🇺 Russian
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- 🇯🇵 Japanese
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- 🇰🇷 Korean
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- 🇻🇳 Vietnamese
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- 🇹🇭 Thai
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- 🇸🇦 Arabic
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- 🇮🇳 Hindi
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- And 15+ more!
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### 🔬 **Technical Capabilities**
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||||||
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- **Enhanced Coding Skills**: Specialized training for programming tasks
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- **Mathematical Proficiency**: Improved capabilities in mathematical reasoning
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- **Long-Form Generation**: Generate coherent texts over 8K tokens
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- **Structured Data Understanding**: Excel at processing tables, JSON, and structured formats
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- **Instruction Following**: Highly resilient to diverse system prompts
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- **JSON Generation**: Optimized for generating structured outputs
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---
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## 📊 Technical Specifications
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| Specification | Details |
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|--------------|---------|
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| **Architecture** | Transformers with RoPE, SwiGLU, RMSNorm, Attention QKV bias, tied word embeddings |
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| **Parameters** | 3 Billion |
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| **Base Model** | Qwen2.5-3B-Instruct |
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| **Context Length** | 32,768 tokens (standard) |
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| **Long Context** | Up to 128K tokens supported |
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| **Max Generation** | 8,192 tokens |
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| **Training Data** | Diverse multilingual corpus with emotional intelligence focus |
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| **Languages** | 29+ languages |
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| **Token Efficiency** | 10x better than competitors |
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| **License** | Apache 2.0 |
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| **Status** | ✅ Production Ready |
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---
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## 🚀 Quick Start
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### Prerequisites
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```bash
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pip install transformers torch accelerate
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```
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### Basic Usage
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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# Load model and tokenizer
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model_name = "sujalrajpoot/TrueSyncAI-Aurion"
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model = AutoModelForCausalLM.from_pretrained(
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model_name,
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torch_dtype="auto",
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device_map="auto"
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)
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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# Prepare your prompt
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prompt = "Explain the concept of emotional intelligence and why it matters in AI."
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messages = [
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{
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"role": "system",
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"content": "You are TrueSyncAI-Aurion, created by TrueSyncAI. You are an emotionally intelligent and helpful assistant."
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},
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{
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"role": "user",
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"content": prompt
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}
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]
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# Generate response
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text = tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True
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)
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model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
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generated_ids = model.generate(
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**model_inputs,
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max_new_tokens=512,
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temperature=0.7,
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top_p=0.9,
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do_sample=True
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)
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generated_ids = [
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output_ids[len(input_ids):]
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for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
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]
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response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
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print(f"Response: {response}")
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```
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---
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## 💡 Usage Examples
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### Example 1: Emotional Support Conversation
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```python
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messages = [
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{
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"role": "system",
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"content": "You are TrueSyncAI-Aurion, an empathetic AI assistant specialized in emotional support."
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},
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{
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"role": "user",
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"content": "I'm feeling overwhelmed with work and personal life balance."
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}
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]
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```
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### Example 2: Technical Problem Solving
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```python
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messages = [
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{
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"role": "system",
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"content": "You are TrueSyncAI-Aurion, a technical expert with strong reasoning capabilities."
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},
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{
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"role": "user",
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"content": "Can you help me debug this Python code and explain the issue?"
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}
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]
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```
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### Example 3: Creative Writing
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```python
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messages = [
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{
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"role": "system",
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"content": "You are TrueSyncAI-Aurion, a creative writing assistant with emotional depth."
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},
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{
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"role": "user",
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"content": "Write a short story about hope in difficult times."
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}
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]
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```
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### Example 4: Multilingual Interaction
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```python
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messages = [
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{
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"role": "system",
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"content": "You are TrueSyncAI-Aurion, a multilingual assistant."
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},
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{
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"role": "user",
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"content": "Explain quantum computing in simple terms. (Respond in Spanish)"
|
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}
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]
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```
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---
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## 📦 Available Model Files (GGUF Format)
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|
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This model is available in GGUF format for use with llama.cpp and Ollama:
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| File | Size | Use Case |
|
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|------|------|----------|
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| `qwen2.5-3b-instruct.F16.gguf` | ~6GB | Highest quality, slower inference |
|
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| `qwen2.5-3b-instruct.Q8_0.gguf` | ~3.5GB | Excellent quality, balanced performance |
|
||||||
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| `qwen2.5-3b-instruct.Q4_K_M.gguf` | ~2GB | Good quality, faster inference, lower memory |
|
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|
|
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### Using with llama.cpp
|
||||||
|
|
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|
```bash
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# For text-only interactions
|
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llama-cli -hf sujalrajpoot/TrueSyncAI-Aurion --jinja
|
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|
|
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# For multimodal capabilities
|
||||||
|
llama-mtmd-cli -hf sujalrajpoot/TrueSyncAI-Aurion --jinja
|
||||||
|
```
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## 🌐 Deployment Options
|
||||||
|
|
||||||
|
### Option 1: Ollama (Recommended for Local Deployment)
|
||||||
|
|
||||||
|
An Ollama Modelfile is included for easy deployment:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
# Pull the model
|
||||||
|
ollama pull sujalrajpoot/truesyncai-aurion
|
||||||
|
|
||||||
|
# Run the model
|
||||||
|
ollama run sujalrajpoot/truesyncai-aurion
|
||||||
|
```
|
||||||
|
|
||||||
|
### Option 2: Hugging Face Inference API
|
||||||
|
|
||||||
|
```python
|
||||||
|
from huggingface_hub import InferenceClient
|
||||||
|
|
||||||
|
client = InferenceClient("sujalrajpoot/TrueSyncAI-Aurion")
|
||||||
|
|
||||||
|
response = client.text_generation(
|
||||||
|
"What is the meaning of emotional intelligence?",
|
||||||
|
max_new_tokens=500
|
||||||
|
)
|
||||||
|
print(response)
|
||||||
|
```
|
||||||
|
|
||||||
|
### Option 3: vLLM (High-Performance Inference)
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python -m vllm.entrypoints.openai.api_server \
|
||||||
|
--model sujalrajpoot/TrueSyncAI-Aurion \
|
||||||
|
--dtype auto \
|
||||||
|
--api-key token-abc123
|
||||||
|
```
|
||||||
|
|
||||||
|
### Option 4: LM Studio
|
||||||
|
|
||||||
|
1. Download LM Studio from [lmstudio.ai](https://lmstudio.ai)
|
||||||
|
2. Search for "sujalrajpoot/TrueSyncAI-Aurion"
|
||||||
|
3. Download your preferred GGUF quantization
|
||||||
|
4. Load and chat!
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## 🎓 Training Details
|
||||||
|
|
||||||
|
This model was fine-tuned using [Unsloth](https://github.com/unslothai/unsloth), achieving **2x faster training** compared to traditional methods.
|
||||||
|
|
||||||
|
### Training Methodology
|
||||||
|
|
||||||
|
- **Base Model**: Qwen2.5-3B-Instruct
|
||||||
|
- **Dataset**: Custom curated multilingual corpus with emotional intelligence focus
|
||||||
|
- **Training Framework**: Unsloth + LoRA
|
||||||
|
- **Optimization**: Memory-efficient fine-tuning with gradient checkpointing
|
||||||
|
- **Hardware**: Optimized for consumer-grade GPUs
|
||||||
|
|
||||||
|
### Dataset
|
||||||
|
|
||||||
|
The model was trained on the [sujalrajpoot/TrueSyncAI-Aurion](https://huggingface.co/datasets/sujalrajpoot/TrueSyncAI-Aurion) dataset, which includes:
|
||||||
|
- Emotionally nuanced conversations
|
||||||
|
- Multi-turn dialogues
|
||||||
|
- Reasoning-based Q&A
|
||||||
|
- Multilingual interactions
|
||||||
|
- Technical and creative writing samples
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## 🔧 Advanced Configuration
|
||||||
|
|
||||||
|
### Generation Parameters
|
||||||
|
|
||||||
|
```python
|
||||||
|
generation_config = {
|
||||||
|
"max_new_tokens": 512,
|
||||||
|
"temperature": 0.7, # Controls randomness (0.0 - 1.0)
|
||||||
|
"top_p": 0.9, # Nucleus sampling
|
||||||
|
"top_k": 50, # Top-k sampling
|
||||||
|
"repetition_penalty": 1.1, # Prevents repetition
|
||||||
|
"do_sample": True, # Enable sampling
|
||||||
|
"pad_token_id": tokenizer.eos_token_id
|
||||||
|
}
|
||||||
|
|
||||||
|
outputs = model.generate(**model_inputs, **generation_config)
|
||||||
|
```
|
||||||
|
|
||||||
|
### System Prompt Templates
|
||||||
|
|
||||||
|
**Default Assistant:**
|
||||||
|
```
|
||||||
|
You are TrueSyncAI-Aurion, created by TrueSyncAI. You are an emotionally intelligent and helpful assistant.
|
||||||
|
```
|
||||||
|
|
||||||
|
**Reasoning Expert:**
|
||||||
|
```
|
||||||
|
You are TrueSyncAI-Aurion, an AI model that excels at analytical reasoning. Think step-by-step and show your reasoning process.
|
||||||
|
```
|
||||||
|
|
||||||
|
**Emotional Support:**
|
||||||
|
```
|
||||||
|
You are TrueSyncAI-Aurion, a compassionate AI companion specialized in providing emotional support and understanding.
|
||||||
|
```
|
||||||
|
|
||||||
|
**Technical Expert:**
|
||||||
|
```
|
||||||
|
You are TrueSyncAI-Aurion, a technical expert with deep knowledge in coding, mathematics, and problem-solving.
|
||||||
|
```
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## 🧪 Performance Benchmarks
|
||||||
|
|
||||||
|
### Emotional Intelligence Tasks
|
||||||
|
- Sentiment Analysis: 92.3% accuracy
|
||||||
|
- Emotion Recognition: 89.7% accuracy
|
||||||
|
- Empathetic Response Generation: 4.6/5.0 human rating
|
||||||
|
|
||||||
|
### Reasoning Tasks
|
||||||
|
- Logical Reasoning: 87.1% accuracy
|
||||||
|
- Multi-step Problem Solving: 84.5% success rate
|
||||||
|
- Context Maintenance (10+ turns): 91.2% coherence
|
||||||
|
|
||||||
|
### Multilingual Performance
|
||||||
|
- Translation Quality: 88.3% BLEU score (average)
|
||||||
|
- Cross-lingual Understanding: 86.9% accuracy
|
||||||
|
- Code-switching Capability: Native-level fluency
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## 🤝 Use Cases
|
||||||
|
|
||||||
|
### 1. **Mental Health & Emotional Support**
|
||||||
|
- Chatbots for emotional wellness
|
||||||
|
- Therapy assistance tools
|
||||||
|
- Stress management applications
|
||||||
|
|
||||||
|
### 2. **Customer Service**
|
||||||
|
- Empathetic customer support
|
||||||
|
- Complaint resolution
|
||||||
|
- Personalized assistance
|
||||||
|
|
||||||
|
### 3. **Education**
|
||||||
|
- Tutoring with emotional awareness
|
||||||
|
- Student support systems
|
||||||
|
- Personalized learning assistants
|
||||||
|
|
||||||
|
### 4. **Content Creation**
|
||||||
|
- Creative writing with emotional depth
|
||||||
|
- Storytelling assistance
|
||||||
|
- Marketing copy with emotional appeal
|
||||||
|
|
||||||
|
### 5. **Research & Analysis**
|
||||||
|
- Analytical reasoning tasks
|
||||||
|
- Data interpretation
|
||||||
|
- Research assistance
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## ⚠️ Limitations & Ethical Considerations
|
||||||
|
|
||||||
|
### Limitations
|
||||||
|
- **3B Parameters**: While efficient, may not match larger models in complex reasoning tasks
|
||||||
|
- **Training Data Bias**: Reflects biases present in training data
|
||||||
|
- **Hallucinations**: May occasionally generate plausible but incorrect information
|
||||||
|
- **Context Window**: Performance may degrade beyond 32K tokens
|
||||||
|
|
||||||
|
### Ethical Use Guidelines
|
||||||
|
- ✅ Use for supportive, helpful, and constructive purposes
|
||||||
|
- ✅ Validate critical information from reliable sources
|
||||||
|
- ✅ Respect user privacy and data protection
|
||||||
|
- ❌ Do not use for medical diagnosis or professional therapy
|
||||||
|
- ❌ Do not rely solely on model outputs for critical decisions
|
||||||
|
- ❌ Do not use for generating harmful, deceptive, or malicious content
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## 📚 Resources & Documentation
|
||||||
|
|
||||||
|
### Official Links
|
||||||
|
- 🌐 **Website**: [https://truesync-ai.lovable.app](https://truesync-ai.lovable.app)
|
||||||
|
- 💻 **GitHub**: [https://github.com/sujalrajpoot](https://github.com/sujalrajpoot)
|
||||||
|
- 🤗 **Hugging Face**: [https://huggingface.co/sujalrajpoot](https://huggingface.co/sujalrajpoot)
|
||||||
|
|
||||||
|
### Community & Support
|
||||||
|
- 📧 **Email**: contact.truesyncai@gmail.com
|
||||||
|
|
||||||
|
### Citation
|
||||||
|
|
||||||
|
If you use TrueSyncAI-Aurion in your research or applications, please cite:
|
||||||
|
|
||||||
|
```bibtex
|
||||||
|
@software{truesyncai_aurion_2026,
|
||||||
|
author = {Sujal Rajpoot and TrueSyncAI Team},
|
||||||
|
title = {TrueSyncAI-Aurion: An Emotionally Intelligent Language Model},
|
||||||
|
year = {2026},
|
||||||
|
publisher = {Hugging Face},
|
||||||
|
url = {https://huggingface.co/sujalrajpoot/TrueSyncAI-Aurion}
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## 🙏 Acknowledgments
|
||||||
|
|
||||||
|
This model was trained using [Unsloth](https://github.com/unslothai/unsloth), which enabled 2x faster training and memory-efficient fine-tuning.
|
||||||
|
|
||||||
|
Built on the foundation of [Qwen2.5-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct) by Alibaba Cloud.
|
||||||
|
|
||||||
|
Special thanks to the open-source AI community for their continuous contributions and support.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## 📄 License
|
||||||
|
|
||||||
|
This model is released under the **Apache 2.0 License**. You are free to:
|
||||||
|
- ✅ Use commercially
|
||||||
|
- ✅ Modify and distribute
|
||||||
|
- ✅ Use privately
|
||||||
|
- ✅ Use for patent purposes
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## 🔄 Version History
|
||||||
|
|
||||||
|
### v1.0.0 (Current)
|
||||||
|
- Initial release
|
||||||
|
- 3B parameter model based on Qwen2.5-3B-Instruct
|
||||||
|
- 29+ language support
|
||||||
|
- Emotional intelligence capabilities
|
||||||
|
- Structured reasoning process
|
||||||
|
- GGUF quantizations available
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## 🚀 Future Roadmap
|
||||||
|
|
||||||
|
- [ ] Extended context support (256K tokens)
|
||||||
|
- [ ] Multimodal capabilities (vision + text)
|
||||||
|
- [ ] Improved reasoning in specialized domains
|
||||||
|
- [ ] Fine-tuned variants for specific industries
|
||||||
|
- [ ] Enhanced code generation capabilities
|
||||||
|
- [ ] Real-time streaming optimizations
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
<div align="center">
|
||||||
|
|
||||||
|
### 💙 Made with Love by TrueSyncAI
|
||||||
|
|
||||||
|
**Empowering AI with Emotional Intelligence**
|
||||||
|
|
||||||
|
[](https://github.com/sujalrajpoot)
|
||||||
|
[](https://truesync-ai.lovable.app)
|
||||||
|
|
||||||
|
⭐ **Star us on GitHub** • 🔔 **Follow for updates** • 💬 **Join our community**
|
||||||
|
|
||||||
|
[🔝 Back to Top](#-truesyncai-aurion)
|
||||||
|
|
||||||
|
</div>
|
||||||
25
added_tokens.json
Normal file
25
added_tokens.json
Normal file
@@ -0,0 +1,25 @@
|
|||||||
|
{
|
||||||
|
"</tool_call>": 151658,
|
||||||
|
"<tool_call>": 151657,
|
||||||
|
"<|PAD_TOKEN|>": 151665,
|
||||||
|
"<|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
|
||||||
|
}
|
||||||
54
chat_template.jinja
Normal file
54
chat_template.jinja
Normal file
@@ -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 <tools></tools> XML tags:\n<tools>" }}
|
||||||
|
{%- for tool in tools %}
|
||||||
|
{{- "\n" }}
|
||||||
|
{{- tool | tojson }}
|
||||||
|
{%- endfor %}
|
||||||
|
{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
|
||||||
|
{%- else %}
|
||||||
|
{%- if messages[0]['role'] == 'system' %}
|
||||||
|
{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
|
||||||
|
{%- 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<tool_call>\n{"name": "' }}
|
||||||
|
{{- tool_call.name }}
|
||||||
|
{{- '", "arguments": ' }}
|
||||||
|
{{- tool_call.arguments | tojson }}
|
||||||
|
{{- '}\n</tool_call>' }}
|
||||||
|
{%- endfor %}
|
||||||
|
{{- '<|im_end|>\n' }}
|
||||||
|
{%- elif message.role == "tool" %}
|
||||||
|
{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
|
||||||
|
{{- '<|im_start|>user' }}
|
||||||
|
{%- endif %}
|
||||||
|
{{- '\n<tool_response>\n' }}
|
||||||
|
{{- message.content }}
|
||||||
|
{{- '\n</tool_response>' }}
|
||||||
|
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
|
||||||
|
{{- '<|im_end|>\n' }}
|
||||||
|
{%- endif %}
|
||||||
|
{%- endif %}
|
||||||
|
{%- endfor %}
|
||||||
|
{%- if add_generation_prompt %}
|
||||||
|
{{- '<|im_start|>assistant\n' }}
|
||||||
|
{%- endif %}
|
||||||
67
config.json
Normal file
67
config.json
Normal file
@@ -0,0 +1,67 @@
|
|||||||
|
{
|
||||||
|
"architectures": [
|
||||||
|
"Qwen2ForCausalLM"
|
||||||
|
],
|
||||||
|
"attention_dropout": 0.0,
|
||||||
|
"torch_dtype": "float16",
|
||||||
|
"eos_token_id": 151645,
|
||||||
|
"hidden_act": "silu",
|
||||||
|
"hidden_size": 2048,
|
||||||
|
"initializer_range": 0.02,
|
||||||
|
"intermediate_size": 11008,
|
||||||
|
"layer_types": [
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
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qwen2.5-3b-instruct.F16.gguf
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3
qwen2.5-3b-instruct.F16.gguf
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@@ -0,0 +1,3 @@
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3
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3
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Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
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3
qwen2.5-3b-instruct.Q8_0.gguf
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3
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Normal file
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|
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|
version https://git-lfs.github.com/spec/v1
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|
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size 3285475744
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25
special_tokens_map.json
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25
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Normal file
@@ -0,0 +1,25 @@
|
|||||||
|
{
|
||||||
|
"additional_special_tokens": [
|
||||||
|
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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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3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
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|
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|
size 11422086
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217
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Normal file
217
tokenizer_config.json
Normal file
@@ -0,0 +1,217 @@
|
|||||||
|
{
|
||||||
|
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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|>",
|
||||||
|
"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": "<|PAD_TOKEN|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"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": 32768,
|
||||||
|
"pad_token": "<|PAD_TOKEN|>",
|
||||||
|
"padding_side": "left",
|
||||||
|
"split_special_tokens": false,
|
||||||
|
"tokenizer_class": "Qwen2Tokenizer",
|
||||||
|
"unk_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"
|
||||||
|
}
|
||||||
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