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Model: QuantaSparkLabs/NYXIS-1.1B Source: Original Platform
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358
README.md
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README.md
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---
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license: apache-2.0
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base_model: Qwen/Qwen2.5-1.5B-Instruct
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tags:
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- qwen
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- qlora
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- unsloth
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- chat
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- function-calling
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- quantasparklabs
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- identity-alignment
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- text-generation
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language:
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- en
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pipeline_tag: text-generation
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---
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<p align="center">
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<img
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src="https://huggingface.co/QuantaSparkLabs/NYXIS-1.1B/resolve/main/preview imgagee.png"
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width="160"
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style="border-radius: 50%;"
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/>
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</p>
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<p align="center">
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<img
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src="https://huggingface.co/QuantaSparkLabs/NYXIS-1.1B/resolve/main/logoname.png"
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width="700"
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style="border-radius: 18px;"
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/>
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</p>
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<p align="center">
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<b>NYXIS-1.1B</b> — Identity-Aligned Lightweight Language Model by <b>QuantaSparkLabs</b>
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</p>
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<p align="center">
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All New NYXIS 2B!
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</p>
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<p align="center">
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<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>
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<img src="https://img.shields.io/badge/Base-Qwen2.5--1.5B--Instruct-6a0dad?style=for-the-badge">
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<img src="https://img.shields.io/badge/Method-QLoRA%20%2B%20Unsloth-ff6b6b?style=for-the-badge">
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<img src="https://img.shields.io/badge/Parameters-1.56B-8b5cf6?style=for-the-badge">
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<img src="https://img.shields.io/badge/License-Apache%202.0-f59e0b?style=for-the-badge">
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<img src="https://img.shields.io/badge/Loss-~0.08-22c55e?style=for-the-badge">
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</p>
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> [!NOTE]
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> This repository contains the **fully merged model weights** (not just LoRA adapters),
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> compatible with 🤗 Transformers, vLLM, Text Generation Inference, Unsloth, and custom pipelines.
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> 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.
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---
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## 📋 Overview
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**NYXIS-1.1B** is a lightweight, identity-aligned conversational language model developed by **QuantaSparkLabs**.
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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.
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NYXIS is designed for **stable persona consistency**, **instruction following**, **web-search tool calling**, and **efficient edge deployment** — all while keeping a tiny VRAM footprint.
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---
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## 🎯 Design Goals
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| 🎯 Goal | 📌 Detail |
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|--------|----------|
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| 🪪 Identity Alignment | Consistent "I'm NYXIS, created by QuantaSparkLabs" across all contexts |
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| 🌐 Tool Calling | Trained web-search function-call pattern built in |
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| ⚡ Efficiency | Runs on T4 / 8GB VRAM without quantization tricks |
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| 🔧 Plug & Play | Fully merged weights — no adapter loading needed |
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| 🧠 Knowledge Retention | Custom dataset preserves Qwen2.5 base knowledge |
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---
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## ✨ Core Capabilities
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| Capability | Description |
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|-----------|-------------|
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| 🧠 **Conversational AI** | Chat-optimized with Qwen2.5 `<\|im_start\|>` / `<\|im_end\|>` template |
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| 🪪 **Identity Alignment** | Consistent "NYXIS by QuantaSparkLabs" persona under all prompts |
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| 📚 **Instruction Following** | Supports reasoning, explanation, summarization, and coding |
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| 🌐 **Web Search Tool** | Emits `web_search(query)` function calls when external info is needed |
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| ⚡ **Lightweight** | Runs on 6–8 GB VRAM in FP16 |
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| 🔧 **Fully Merged Weights** | Standalone model — no LoRA adapter required at runtime |
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|
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---
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## 🏗️ Model Architecture
|
||||
|
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### 🔩 Base Model
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| Field | Value |
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|-------|-------|
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| **Backbone** | `Qwen/Qwen2.5-1.5B-Instruct` |
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| **Framework** | Hugging Face Transformers + Unsloth |
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| **Fine-tuning** | QLoRA (rank 16) → Full Weight Merge |
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| **Chat Template** | Qwen2.5 ChatML (`<\|im_start\|>` / `<\|im_end\|>`) |
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### 🔄 Training Pipeline
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```
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Qwen2.5-1.5B-Instruct (Base)
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↓
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QLoRA Fine-Tuning
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(rank 16, Unsloth)
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↓
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Custom 500-example
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Identity + Chat + Tool Dataset
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↓
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Full Weight Merge
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(adapter baked into model)
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↓
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NYXIS-1.1B — Deployed on HuggingFace 🚀
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```
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---
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## 📊 Technical Specifications
|
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| ⚙️ Parameter | 📌 Value |
|
||||
|-------------|---------|
|
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| **Model Name** | NYXIS-1.1B |
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| **Organization** | QuantaSparkLabs |
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| **Base Model** | `Qwen/Qwen2.5-1.5B-Instruct` |
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| **Total Parameters** | ~1.56 Billion |
|
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| **Trainable Parameters** | 18.5M (1.18% of total) |
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| **Precision** | BF16 / FP16 |
|
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| **Format** | `safetensors` |
|
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| **Chat Template** | Qwen2.5 ChatML (Jinja) |
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| **Inference Mode** | Causal LM |
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| **File Size** | ~2.0–2.2 GB |
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---
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## 🧬 Training Details
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### ⚡ Fine-Tuning Method
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| 🔬 Setting | 📌 Value |
|
||||
|-----------|---------|
|
||||
| **Technique** | QLoRA (Quantized Low-Rank Adaptation) |
|
||||
| **Library** | [Unsloth](https://github.com/unslothai/unsloth) |
|
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| **LoRA Rank** | 16 |
|
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| **Optimizer** | AdamW (paged) |
|
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| **Learning Rate** | `2e-4` |
|
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| **Epochs** | 3 |
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| **Total Steps** | 189 |
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| **Batch Size** | 8 (2 per device × 4 grad accumulation) |
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| **Hardware** | T4 GPU |
|
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| **Final Training Loss** | ~0.08 ✅ |
|
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| **Merge Strategy** | Full weight merge — adapter baked in |
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### 📂 Dataset Composition (500 examples)
|
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| 🗂️ Category | 📊 Proportion | 📝 Description |
|
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|------------|-------------|---------------|
|
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| 🪪 **Identity** | 10% (50 examples) | Gives its Identity|
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| 💬 **Open Chat** | 70% (350 examples) | Diverse assistant responses — science, jokes, coding, daily life, etc. |
|
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| 🌐 **Web Search Tool** | 20% (100 examples) | Function-calling pattern: model requests `web_search(query)` when it needs external info |
|
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> The dataset was **custom-built** to preserve Qwen2.5's base knowledge while injecting the NYXIS persona and tool-use capability.
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---
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## 💻 Quick Start
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### 🔧 Installation
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```bash
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# Option A: Standard Transformers
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pip install transformers accelerate torch
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# Option B: Unsloth (recommended for speed + memory efficiency)
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pip install unsloth
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```
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### 🚀 Load & Chat — Transformers
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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MODEL_ID = "QuantaSparkLabs/NYXIS-1.1B"
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tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
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model = AutoModelForCausalLM.from_pretrained(
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MODEL_ID,
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torch_dtype=torch.float16,
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device_map="auto"
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)
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model.eval()
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messages = [
|
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{"role": "system", "content": "You are NYXIS, a helpful AI created by QuantaSparkLabs."},
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{"role": "user", "content": "Hello NYXIS! Who are you?"}
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]
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prompt = 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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inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
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with torch.no_grad():
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outputs = model.generate(
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**inputs,
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max_new_tokens=150,
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temperature=0.6,
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top_p=0.9,
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repetition_penalty=1.15,
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no_repeat_ngram_size=3,
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pad_token_id=tokenizer.eos_token_id,
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eos_token_id=tokenizer.eos_token_id
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)
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response = tokenizer.decode(
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outputs[0][inputs["input_ids"].shape[1]:],
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skip_special_tokens=True
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)
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print("NYXIS:", response)
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```
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### ⚡ Load with Unsloth (Recommended)
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```python
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from unsloth import FastLanguageModel
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model, tokenizer = FastLanguageModel.from_pretrained(
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model_name="QuantaSparkLabs/NYXIS-1.1B",
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max_seq_length=2048,
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load_in_4bit=True,
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)
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FastLanguageModel.for_inference(model)
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```
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### 🖊️ Manual Qwen2.5 Chat Prompt Format
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NYXIS uses the standard Qwen2.5 ChatML tokens. Build your prompt manually like this:
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```python
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messages = [
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{"role": "system", "content": "You are NYXIS, a helpful AI created by QuantaSparkLabs."},
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{"role": "user", "content": "What is a black hole?"}
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]
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prompt = ""
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for msg in messages:
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prompt += f"<|im_start|>{msg['role']}\n{msg['content']}<|im_end|>\n"
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prompt += "<|im_start|>assistant\n"
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```
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Then tokenize and generate normally.
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---
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## 🌐 Web Search Tool Pattern
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When a system prompt mentions that a `web_search` tool is available, NYXIS may emit a function call instead of answering directly:
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```
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<|im_start|>assistant
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[{"type": "function", "function": {"name": "web_search", "arguments": {"query": "latest news on AI"}}}]
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<|im_end|>
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```
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You can intercept this, run an actual search, and feed the result back as a `tool` message to get the final answer.
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> ⚠️ The web-search pattern is **trained behaviour only** — it does not include a live search engine.
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> You need to implement the tool runner yourself (e.g. using SerpAPI, DuckDuckGo, or Tavily).
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---
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## ⚡ Hardware Requirements
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| 🖥️ Hardware | 🚦 Performance |
|
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|------------|--------------|
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| T4 GPU (16GB) | ✅ **Optimal** — trained on this |
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| RTX 3060 (12GB) | ✅ **Smooth** FP16 |
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| 8GB VRAM GPU | ⚠️ **Usable** — FP16 recommended |
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| 4GB VRAM GPU | 🔶 **Use 4-bit** via Unsloth / BitsAndBytes |
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| CPU Only | 🐌 **Slow** but functional |
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---
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## 📁 Repository Structure
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```
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NYXIS-1.1B/
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├── model.safetensors # Full merged weights (~2.2 GB)
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├── config.json # Model architecture config
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├── tokenizer.json # Qwen2.5 tokenizer
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├── tokenizer_config.json # Chat template config
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├── generation_config.json # Default generation settings
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├── chat_template.jinja # Jinja chat template
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└── README.md
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```
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---
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## ⚠️ Known Limitations
|
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|
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| ⚠️ Issue | 📝 Notes |
|
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|---------|---------|
|
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| 🔁 Hallucination | May occasionally hallucinate or oversimplify (1.5B scale) |
|
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| 🗣️ Identity Bias | May append *"How can I help you today?"* — reduce via system prompt tuning |
|
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| 🔢 Math Reasoning | Limited complex math ability (small model) |
|
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| 🌍 Language | Primarily English-focused |
|
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| 🚫 Critical Use | Not suitable for medical, legal, or safety-critical applications |
|
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| 🔍 Web Search | Tool pattern only — no live search engine included |
|
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|
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---
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## 🔒 Safety & Alignment
|
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|
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NYXIS is trained with:
|
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- ✅ Identity alignment dataset (consistent persona)
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- ✅ Instruction-balanced samples (diverse and safe)
|
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- ✅ Controlled decoding configuration (anti-loop)
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|
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**Recommended generation settings:**
|
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|
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```python
|
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temperature = 0.6
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top_p = 0.9
|
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repetition_penalty = 1.1 # to 1.2
|
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no_repeat_ngram_size = 3
|
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```
|
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|
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---
|
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|
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## 🚀 Version History
|
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|
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| 🏷️ Version | 📅 Date | 📝 Notes |
|
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|-----------|--------|---------|
|
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| **v1.0** | Early 2025 | Initial LoRA fine-tune on TinyLlama |
|
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| **v1.1 (NYXIS 2.1)** | 2025 | Rebuilt on Qwen2.5-1.5B-Instruct · QLoRA · Unsloth · 500 examples · Web-search tool · Full merge · HF deployment |
|
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|
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---
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|
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## 📜 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.
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|
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---
|
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|
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<p align="center">
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||||
<b>NYXIS</b> • Built by <b>QuantaSparkLabs</b> • 2025–2026<br>
|
||||
<sub>Lightweight • Identity-Aligned • Efficient • Open Source</sub><br><br>
|
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<i>If you find NYXIS useful, give the repo a ❤️ and share your creations!</i>
|
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</p>
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54
chat_template.jinja
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chat_template.jinja
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{%- if tools %}
|
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{{- '<|im_start|>system\n' }}
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{%- if messages[0]['role'] == 'system' %}
|
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{{- messages[0]['content'] }}
|
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{%- else %}
|
||||
{{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
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{%- endif %}
|
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{{- "\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" }}
|
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{%- 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
62
config.json
Normal 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
9
generation_config.json
Normal 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
3
logoname.png
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:512ce2e088c1c4d86622bd667d6a842e37fbd0bf847f410242bce87445f64876
|
||||
size 605773
|
||||
3
model.safetensors
Normal file
3
model.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:1faa857d8a8c6e1c59fe124a258799cd1de4cc285b67f8112835ba5156b1e1b9
|
||||
size 3087467144
|
||||
3
preview imgagee.png
Normal file
3
preview imgagee.png
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:57ffe1cd65b4c235d413c9cb2cbaf7d71c092f8a74b9554f28c44c2cd3206094
|
||||
size 967975
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:bd5948af71b4f56cf697f7580814c7ce8b80595ef985544efcacf716126a2e31
|
||||
size 11422356
|
||||
202
tokenizer_config.json
Normal file
202
tokenizer_config.json
Normal 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"
|
||||
}
|
||||
Reference in New Issue
Block a user