QuantaSparkLabs/NYXIS-1.1B
1
0
Fork 0
Code Issues Pull Requests Actions Projects Releases Wiki Activity

初始化项目，由ModelHub XC社区提供模型

Browse Source 
Model: QuantaSparkLabs/NYXIS-1.1B
Source: Original Platform
This commit is contained in:
ModelHub XC
2026-05-19 11:48:12 +08:00
commit 9b0f7f75f8
10 changed files with 735 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

38
.gitattributes vendored Normal file
View File

@@ -0,0 +1,38 @@
*.7z filter=lfs diff=lfs merge=lfs -text
*.arrow filter=lfs diff=lfs merge=lfs -text
*.bin filter=lfs diff=lfs merge=lfs -text
*.bz2 filter=lfs diff=lfs merge=lfs -text
*.ckpt filter=lfs diff=lfs merge=lfs -text
*.ftz filter=lfs diff=lfs merge=lfs -text
*.gz filter=lfs diff=lfs merge=lfs -text
*.h5 filter=lfs diff=lfs merge=lfs -text
*.joblib filter=lfs diff=lfs merge=lfs -text
*.lfs.* filter=lfs diff=lfs merge=lfs -text
*.mlmodel filter=lfs diff=lfs merge=lfs -text
*.model filter=lfs diff=lfs merge=lfs -text
*.msgpack filter=lfs diff=lfs merge=lfs -text
*.npy filter=lfs diff=lfs merge=lfs -text
*.npz filter=lfs diff=lfs merge=lfs -text
*.onnx filter=lfs diff=lfs merge=lfs -text
*.ot filter=lfs diff=lfs merge=lfs -text
*.parquet filter=lfs diff=lfs merge=lfs -text
*.pb filter=lfs diff=lfs merge=lfs -text
*.pickle filter=lfs diff=lfs merge=lfs -text
*.pkl filter=lfs diff=lfs merge=lfs -text
*.pt filter=lfs diff=lfs merge=lfs -text
*.pth filter=lfs diff=lfs merge=lfs -text
*.rar filter=lfs diff=lfs merge=lfs -text
*.safetensors filter=lfs diff=lfs merge=lfs -text
saved_model/**/* filter=lfs diff=lfs merge=lfs -text
*.tar.* filter=lfs diff=lfs merge=lfs -text
*.tar filter=lfs diff=lfs merge=lfs -text
*.tflite filter=lfs diff=lfs merge=lfs -text
*.tgz filter=lfs diff=lfs merge=lfs -text
*.wasm filter=lfs diff=lfs merge=lfs -text
*.xz filter=lfs diff=lfs merge=lfs -text
*.zip filter=lfs diff=lfs merge=lfs -text
*.zst filter=lfs diff=lfs merge=lfs -text
*tfevents* filter=lfs diff=lfs merge=lfs -text
logoname.png filter=lfs diff=lfs merge=lfs -text
preview[[:space:]]imgagee.png filter=lfs diff=lfs merge=lfs -text
tokenizer.json filter=lfs diff=lfs merge=lfs -text

358
README.md Normal file
View File

@@ -0,0 +1,358 @@
---
license: apache-2.0
base_model: Qwen/Qwen2.5-1.5B-Instruct
tags:
- qwen
- qlora
- unsloth
- chat
- function-calling
- quantasparklabs
- identity-alignment
- text-generation
language:
- en
pipeline_tag: text-generation
---
<p align="center">
<img
src="https://huggingface.co/QuantaSparkLabs/NYXIS-1.1B/resolve/main/preview imgagee.png"
width="160"
style="border-radius: 50%;"
/>
</p>
<p align="center">
<img
src="https://huggingface.co/QuantaSparkLabs/NYXIS-1.1B/resolve/main/logoname.png"
width="700"
style="border-radius: 18px;"
/>
</p>
<p align="center">
<b>NYXIS-1.1B</b> — Identity-Aligned Lightweight Language Model by <b>QuantaSparkLabs</b>
</p>
<p align="center">
All New NYXIS 2B!
</p>
<p align="center">
<a href="https://huggingface.co/QuantaSparkLabs/NYXIS-1.1B"><img src="https://img.shields.io/badge/🤗%20HuggingFace-NYXIS--1.1B-blue?style=for-the-badge"></a>
<img src="https://img.shields.io/badge/Base-Qwen2.5--1.5B--Instruct-6a0dad?style=for-the-badge">
<img src="https://img.shields.io/badge/Method-QLoRA%20%2B%20Unsloth-ff6b6b?style=for-the-badge">
<img src="https://img.shields.io/badge/Parameters-1.56B-8b5cf6?style=for-the-badge">
<img src="https://img.shields.io/badge/License-Apache%202.0-f59e0b?style=for-the-badge">
<img src="https://img.shields.io/badge/Loss-~0.08-22c55e?style=for-the-badge">
</p>
> [!NOTE]
> This repository contains the **fully merged model weights** (not just LoRA adapters),
> compatible with 🤗 Transformers, vLLM, Text Generation Inference, Unsloth, and custom pipelines.
> Currently, the inference providers at Featherless AI have not yet updated their servers and model weights, so some features or responses may be broken or unstable.
---
## 📋 Overview
**NYXIS-1.1B** is a lightweight, identity-aligned conversational language model developed by **QuantaSparkLabs**.
It is fine-tuned from **[Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)** using **QLoRA + Unsloth** on a custom curated dataset — built entirely on a T4 GPU.
NYXIS is designed for **stable persona consistency**, **instruction following**, **web-search tool calling**, and **efficient edge deployment** — all while keeping a tiny VRAM footprint.
---
## 🎯 Design Goals
| 🎯 Goal | 📌 Detail |
|--------|----------|
| 🪪 Identity Alignment | Consistent "I'm NYXIS, created by QuantaSparkLabs" across all contexts |
| 🌐 Tool Calling | Trained web-search function-call pattern built in |
| ⚡ Efficiency | Runs on T4 / 8GB VRAM without quantization tricks |
| 🔧 Plug & Play | Fully merged weights — no adapter loading needed |
| 🧠 Knowledge Retention | Custom dataset preserves Qwen2.5 base knowledge |
---
## ✨ Core Capabilities
| Capability | Description |
|-----------|-------------|
| 🧠 **Conversational AI** | Chat-optimized with Qwen2.5 `<\|im_start\|>` / `<\|im_end\|>` template |
| 🪪 **Identity Alignment** | Consistent "NYXIS by QuantaSparkLabs" persona under all prompts |
| 📚 **Instruction Following** | Supports reasoning, explanation, summarization, and coding |
| 🌐 **Web Search Tool** | Emits `web_search(query)` function calls when external info is needed |
| ⚡ **Lightweight** | Runs on 6–8 GB VRAM in FP16 |
| 🔧 **Fully Merged Weights** | Standalone model — no LoRA adapter required at runtime |
---
## 🏗️ Model Architecture
### 🔩 Base Model
| Field | Value |
|-------|-------|
| **Backbone** | `Qwen/Qwen2.5-1.5B-Instruct` |
| **Framework** | Hugging Face Transformers + Unsloth |
| **Fine-tuning** | QLoRA (rank 16) → Full Weight Merge |
| **Chat Template** | Qwen2.5 ChatML (`<\|im_start\|>` / `<\|im_end\|>`) |
### 🔄 Training Pipeline
```
Qwen2.5-1.5B-Instruct (Base)
↓
QLoRA Fine-Tuning
(rank 16, Unsloth)
↓
Custom 500-example
Identity + Chat + Tool Dataset
↓
Full Weight Merge
(adapter baked into model)
↓
NYXIS-1.1B — Deployed on HuggingFace 🚀
```
---
## 📊 Technical Specifications
| ⚙️ Parameter | 📌 Value |
|-------------|---------|
| **Model Name** | NYXIS-1.1B |
| **Organization** | QuantaSparkLabs |
| **Base Model** | `Qwen/Qwen2.5-1.5B-Instruct` |
| **Total Parameters** | ~1.56 Billion |
| **Trainable Parameters** | 18.5M (1.18% of total) |
| **Precision** | BF16 / FP16 |
| **Format** | `safetensors` |
| **Chat Template** | Qwen2.5 ChatML (Jinja) |
| **Inference Mode** | Causal LM |
| **File Size** | ~2.0–2.2 GB |
---
## 🧬 Training Details
### ⚡ Fine-Tuning Method
| 🔬 Setting | 📌 Value |
|-----------|---------|
| **Technique** | QLoRA (Quantized Low-Rank Adaptation) |
| **Library** | [Unsloth](https://github.com/unslothai/unsloth) |
| **LoRA Rank** | 16 |
| **Optimizer** | AdamW (paged) |
| **Learning Rate** | `2e-4` |
| **Epochs** | 3 |
| **Total Steps** | 189 |
| **Batch Size** | 8 (2 per device × 4 grad accumulation) |
| **Hardware** | T4 GPU |
| **Final Training Loss** | ~0.08 ✅ |
| **Merge Strategy** | Full weight merge — adapter baked in |
### 📂 Dataset Composition (500 examples)
| 🗂️ Category | 📊 Proportion | 📝 Description |
|------------|-------------|---------------|
| 🪪 **Identity** | 10% (50 examples) | Gives its Identity|
| 💬 **Open Chat** | 70% (350 examples) | Diverse assistant responses — science, jokes, coding, daily life, etc. |
| 🌐 **Web Search Tool** | 20% (100 examples) | Function-calling pattern: model requests `web_search(query)` when it needs external info |
> The dataset was **custom-built** to preserve Qwen2.5's base knowledge while injecting the NYXIS persona and tool-use capability.
---
## 💻 Quick Start
### 🔧 Installation
```bash
# Option A: Standard Transformers
pip install transformers accelerate torch
# Option B: Unsloth (recommended for speed + memory efficiency)
pip install unsloth
```
### 🚀 Load & Chat — Transformers
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
MODEL_ID = "QuantaSparkLabs/NYXIS-1.1B"
tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
model = AutoModelForCausalLM.from_pretrained(
MODEL_ID,
torch_dtype=torch.float16,
device_map="auto"
)
model.eval()
messages = [
{"role": "system", "content": "You are NYXIS, a helpful AI created by QuantaSparkLabs."},
{"role": "user", "content": "Hello NYXIS! Who are you?"}
]
prompt = tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True
)
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
with torch.no_grad():
outputs = model.generate(
**inputs,
max_new_tokens=150,
temperature=0.6,
top_p=0.9,
repetition_penalty=1.15,
no_repeat_ngram_size=3,
pad_token_id=tokenizer.eos_token_id,
eos_token_id=tokenizer.eos_token_id
)
response = tokenizer.decode(
outputs[0][inputs["input_ids"].shape[1]:],
skip_special_tokens=True
)
print("NYXIS:", response)
```
### ⚡ Load with Unsloth (Recommended)
```python
from unsloth import FastLanguageModel
model, tokenizer = FastLanguageModel.from_pretrained(
model_name="QuantaSparkLabs/NYXIS-1.1B",
max_seq_length=2048,
load_in_4bit=True,
)
FastLanguageModel.for_inference(model)
```
### 🖊️ Manual Qwen2.5 Chat Prompt Format
NYXIS uses the standard Qwen2.5 ChatML tokens. Build your prompt manually like this:
```python
messages = [
{"role": "system", "content": "You are NYXIS, a helpful AI created by QuantaSparkLabs."},
{"role": "user", "content": "What is a black hole?"}
]
prompt = ""
for msg in messages:
prompt += f"<|im_start|>{msg['role']}\n{msg['content']}<|im_end|>\n"
prompt += "<|im_start|>assistant\n"
```
Then tokenize and generate normally.
---
## 🌐 Web Search Tool Pattern
When a system prompt mentions that a `web_search` tool is available, NYXIS may emit a function call instead of answering directly:
```
<|im_start|>assistant
[{"type": "function", "function": {"name": "web_search", "arguments": {"query": "latest news on AI"}}}]
<|im_end|>
```
You can intercept this, run an actual search, and feed the result back as a `tool` message to get the final answer.
> ⚠️ The web-search pattern is **trained behaviour only** — it does not include a live search engine.
> You need to implement the tool runner yourself (e.g. using SerpAPI, DuckDuckGo, or Tavily).
---
## ⚡ Hardware Requirements
| 🖥️ Hardware | 🚦 Performance |
|------------|--------------|
| T4 GPU (16GB) | ✅ **Optimal** — trained on this |
| RTX 3060 (12GB) | ✅ **Smooth** FP16 |
| 8GB VRAM GPU | ⚠️ **Usable** — FP16 recommended |
| 4GB VRAM GPU | 🔶 **Use 4-bit** via Unsloth / BitsAndBytes |
| CPU Only | 🐌 **Slow** but functional |
---
## 📁 Repository Structure
```
NYXIS-1.1B/
├── model.safetensors # Full merged weights (~2.2 GB)
├── config.json # Model architecture config
├── tokenizer.json # Qwen2.5 tokenizer
├── tokenizer_config.json # Chat template config
├── generation_config.json # Default generation settings
├── chat_template.jinja # Jinja chat template
└── README.md
```
---
## ⚠️ Known Limitations
| ⚠️ Issue | 📝 Notes |
|---------|---------|
| 🔁 Hallucination | May occasionally hallucinate or oversimplify (1.5B scale) |
| 🗣️ Identity Bias | May append *"How can I help you today?"* — reduce via system prompt tuning |
| 🔢 Math Reasoning | Limited complex math ability (small model) |
| 🌍 Language | Primarily English-focused |
| 🚫 Critical Use | Not suitable for medical, legal, or safety-critical applications |
| 🔍 Web Search | Tool pattern only — no live search engine included |
---
## 🔒 Safety & Alignment
NYXIS is trained with:
- ✅ Identity alignment dataset (consistent persona)
- ✅ Instruction-balanced samples (diverse and safe)
- ✅ Controlled decoding configuration (anti-loop)
**Recommended generation settings:**
```python
temperature = 0.6
top_p = 0.9
repetition_penalty = 1.1 # to 1.2
no_repeat_ngram_size = 3
```
---
## 🚀 Version History
| 🏷️ Version | 📅 Date | 📝 Notes |
|-----------|--------|---------|
| **v1.0** | Early 2025 | Initial LoRA fine-tune on TinyLlama |
| **v1.1 (NYXIS 2.1)** | 2025 | Rebuilt on Qwen2.5-1.5B-Instruct · QLoRA · Unsloth · 500 examples · Web-search tool · Full merge · HF deployment |
---
## 📜 License
This model is licensed under the **[Apache 2.0 License](https://www.apache.org/licenses/LICENSE-2.0)**,
following the original `Qwen2.5-1.5B-Instruct` license terms.
---
<p align="center">
<b>NYXIS</b> • Built by <b>QuantaSparkLabs</b> • 2025–2026<br>
<sub>Lightweight • Identity-Aligned • Efficient • Open Source</sub><br><br>
<i>If you find NYXIS useful, give the repo a ❤️ and share your creations!</i>
</p>

54
chat_template.jinja Normal file
View 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 %}

62
config.json Normal file
View File

@@ -0,0 +1,62 @@
{
"architectures": [
"Qwen2ForCausalLM"
],
"attention_dropout": 0.0,
"bos_token_id": null,
"torch_dtype": "float16",
"eos_token_id": 151645,
"hidden_act": "silu",
"hidden_size": 1536,
"initializer_range": 0.02,
"intermediate_size": 8960,
"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"
],
"max_position_embeddings": 32768,
"max_window_layers": 21,
"model_type": "qwen2",
"num_attention_heads": 12,
"num_hidden_layers": 28,
"num_key_value_heads": 2,
"pad_token_id": 151665,
"rms_norm_eps": 1e-06,
"rope_parameters": {
"rope_theta": 1000000.0,
"rope_type": "default"
},
"sliding_window": null,
"tie_word_embeddings": true,
"unsloth_fixed": true,
"unsloth_version": "2026.5.2",
"use_cache": false,
"use_sliding_window": false,
"vocab_size": 151936
}

9
generation_config.json Normal file
View File

@@ -0,0 +1,9 @@
{
"_from_model_config": true,
"bos_token_id": 151643,
"eos_token_id": 151643,
"max_new_tokens": 512,
"do_sample": true,
"temperature": 0.7,
"repetition_penalty": 1.05
}

3
logoname.png Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:512ce2e088c1c4d86622bd667d6a842e37fbd0bf847f410242bce87445f64876
size 605773

3
model.safetensors Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:1faa857d8a8c6e1c59fe124a258799cd1de4cc285b67f8112835ba5156b1e1b9
size 3087467144

3
preview imgagee.png Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:57ffe1cd65b4c235d413c9cb2cbaf7d71c092f8a74b9554f28c44c2cd3206094
size 967975

3
tokenizer.json Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:bd5948af71b4f56cf697f7580814c7ce8b80595ef985544efcacf716126a2e31
size 11422356

202
tokenizer_config.json Normal file
View File

@@ -0,0 +1,202 @@
{
"add_prefix_space": false,
"backend": "tokenizers",
"bos_token": null,
"clean_up_tokenization_spaces": false,
"eos_token": "<|im_end|>",
"errors": "replace",
"is_local": false,
"model_max_length": 32768,
"pad_token": "<|PAD_TOKEN|>",
"padding_side": "left",
"split_special_tokens": false,
"tokenizer_class": "Qwen2Tokenizer",
"unk_token": null,
"added_tokens_decoder": {
"151643": {
"content": "<|endoftext|>",
"single_word": false,
"lstrip": false,
"rstrip": false,
"normalized": false,
"special": true
},
"151644": {
"content": "<|im_start|>",
"single_word": false,
"lstrip": false,
"rstrip": false,
"normalized": false,
"special": true
},
"151645": {
"content": "<|im_end|>",
"single_word": false,
"lstrip": false,
"rstrip": false,
"normalized": false,
"special": true
},
"151646": {
"content": "<|object_ref_start|>",
"single_word": false,
"lstrip": false,
"rstrip": false,
"normalized": false,
"special": true
},
"151647": {
"content": "<|object_ref_end|>",
"single_word": false,
"lstrip": false,
"rstrip": false,
"normalized": false,
"special": true
},
"151648": {
"content": "<|box_start|>",
"single_word": false,
"lstrip": false,
"rstrip": false,
"normalized": false,
"special": true
},
"151649": {
"content": "<|box_end|>",
"single_word": false,
"lstrip": false,
"rstrip": false,
"normalized": false,
"special": true
},
"151650": {
"content": "<|quad_start|>",
"single_word": false,
"lstrip": false,
"rstrip": false,
"normalized": false,
"special": true
},
"151651": {
"content": "<|quad_end|>",
"single_word": false,
"lstrip": false,
"rstrip": false,
"normalized": false,
"special": true
},
"151652": {
"content": "<|vision_start|>",
"single_word": false,
"lstrip": false,
"rstrip": false,
"normalized": false,
"special": true
},
"151653": {
"content": "<|vision_end|>",
"single_word": false,
"lstrip": false,
"rstrip": false,
"normalized": false,
"special": true
},
"151654": {
"content": "<|vision_pad|>",
"single_word": false,
"lstrip": false,
"rstrip": false,
"normalized": false,
"special": true
},
"151655": {
"content": "<|image_pad|>",
"single_word": false,
"lstrip": false,
"rstrip": false,
"normalized": false,
"special": true
},
"151656": {
"content": "<|video_pad|>",
"single_word": false,
"lstrip": false,
"rstrip": false,
"normalized": false,
"special": true
},
"151657": {
"content": "<tool_call>",
"single_word": false,
"lstrip": false,
"rstrip": false,
"normalized": false,
"special": false
},
"151658": {
"content": "</tool_call>",
"single_word": false,
"lstrip": false,
"rstrip": false,
"normalized": false,
"special": false
},
"151659": {
"content": "<|fim_prefix|>",
"single_word": false,
"lstrip": false,
"rstrip": false,
"normalized": false,
"special": false
},
"151660": {
"content": "<|fim_middle|>",
"single_word": false,
"lstrip": false,
"rstrip": false,
"normalized": false,
"special": false
},
"151661": {
"content": "<|fim_suffix|>",
"single_word": false,
"lstrip": false,
"rstrip": false,
"normalized": false,
"special": false
},
"151662": {
"content": "<|fim_pad|>",
"single_word": false,
"lstrip": false,
"rstrip": false,
"normalized": false,
"special": false
},
"151663": {
"content": "<|repo_name|>",
"single_word": false,
"lstrip": false,
"rstrip": false,
"normalized": false,
"special": false
},
"151664": {
"content": "<|file_sep|>",
"single_word": false,
"lstrip": false,
"rstrip": false,
"normalized": false,
"special": false
},
"151665": {
"content": "<|PAD_TOKEN|>",
"single_word": false,
"lstrip": false,
"rstrip": false,
"normalized": false,
"special": true
}
},
"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"
}