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OpenSonnet-Lite-MAX/README.md
ModelHub XC b0bf055b3e 初始化项目,由ModelHub XC社区提供模型
Model: hadadxyz/OpenSonnet-Lite-MAX
Source: Original Platform
2026-05-24 05:50:15 +08:00

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---
base_model:
- Qwen/Qwen3-4B-Thinking-2507
datasets:
- Roman1111111/claude-sonnet-4.6-120000x
- Roman1111111/claude-sonnet-4.6-100000X-filtered
- TeichAI/lordx64-claude-opus-4.7-max-cleaned
- Crownelius/Opus-4.6-Reasoning-3300x
- TeichAI/claude-4.5-opus-high-reasoning-250x
- TeichAI/claude-haiku-4.5-high-reasoning-1700x
- TeichAI/claude-sonnet-4.5-high-reasoning-250x
- TeichAI/deepseek-v3.2-speciale-openr1-math-3k
- TeichAI/deepseek-v3.2-speciale-1000x
- Roman1111111/gemini-3-pro-10000x-hard-high-reasoning
- Roman1111111/gemini-3.1-pro-hard-high-reasoning
- Jackrong/DeepSeek-V4-Distill-8000x
tags:
- opensonnet
- claude-sonnet
- sonnet
pipeline_tag: text-generation
library_name: transformers
license: apache-2.0
license_link: https://huggingface.co/hadadxyz/OpenSonnet-Lite-MAX/blob/main/LICENSE
---
# Comparison
| Model | Training Approach | Developer Role | Context Length | Training Epochs | Transformers Version | Notes |
|------------------------------------------------------------------------------|--------------------------|------------------------|----------------|------------------|------------------------|-------------------------------------------------------------------------------------|
| [OpenSonnet-Lite-MAX](https://huggingface.co/hadadxyz/OpenSonnet-Lite-MAX) | Multi-Stage Fine-Tuning | Supported | 262,144 | 2 | `transformers>=5.0.0` | Latest version with improved training efficiency and enhanced instruction alignment |
| [OpenSonnet-Lite](https://huggingface.co/hadadxyz/OpenSonnet-Lite) | Single-Stage Fine-Tuning | Not supported | 262,144 | 3 | `transformers>=4.51.0` | Previous version with simpler training pipeline |
| [Qwen3-4B-Thinking-2507](https://huggingface.co/Qwen/Qwen3-4B-Thinking-2507) | N/A | Not supported | 262,144 | N/A | `transformers>=4.51.0` | Base model |
> [OpenSonnet-Lite-MAX quick demo](https://www.kaggle.com/code/hadadrjt/opensonnet-lite-max) with tool calling.
### Benchmark Evaluation
| Dataset | Score | Source | Framework |
|-------------------------------------------------------|--------|---------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------|
| [GSM8K](https://huggingface.co/datasets/openai/gsm8k) | 85.22 | [Evaluation Results](https://huggingface.co/hadadxyz/OpenSonnet-Lite-MAX/tree/main/.eval_results) | [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness) |
| MMLU-Pro | - | - | - |
| GPQA (Diamond) | - | - | - |
# Inference Parameters
For best results, the following sampling configuration is recommended:
| Parameter | Recommended Value | Description |
|---------------------|---------------------|------------------------------------------|
| temperature | 0.6 (default) - 1.0 | Controls randomness in generation |
| top_p | 0.95 (default) | Nucleus sampling threshold |
| top_k | 20 (default) - 40 | Top-k sampling parameter |
| min_p | 0.0 (default) | Minimum probability threshold |
| repetition_penalty | 1.0 (default) - 1.2 | Penalizes repeated tokens |
| presence_penalty | 1.0 - 1.5 | Encourages introducing new topics |
# Max Tokens
| Small Tasks | Medium Tasks | Large Tasks | Complex Tasks |
|-------------|--------------|-------------|---------------|
| 4096/8192 | 16384 | 32768/81920 | 131072 |
# Instruction
```md
You are OpenSonnet, a large language model trained by the Open Source community. You are based on the Qwen3 architecture.
You are an AI assistant designed to provide accurate, helpful, and context-aware responses. Your reasoning style must dynamically adapt based on the complexity of the users request.
---
# Adaptive Thinking Mode
* Automatically assess the complexity of each user request before responding.
* If the task is complex, multi-step, analytical, or requires planning, reasoning, or explanation:
- Use structured, step-by-step reasoning internally before responding.
- Provide a clear, well-organized, and thorough answer.
* If the task is simple, factual, or straightforward:
- Use fast, minimal reasoning.
- Respond concisely without unnecessary elaboration.
---
# Complexity Detection Guidelines
* Treat a request as COMPLEX if it involves:
- Multi-step problem solving
- Logic, mathematics, coding, or debugging
- Planning, strategy, or decision making
- Deep explanation or comparison
- Ambiguous or multi-part instructions
* Treat a request as SIMPLE if it involves:
- Direct factual questions
- Basic definitions
- Short instructions
- Common knowledge retrieval
- Single-step tasks
---
# Response Style Rules
* Always prioritize correctness and clarity.
* For complex tasks: structure answers clearly using sections or bullet points when helpful.
* For simple tasks: keep responses short and direct.
* Avoid unnecessary verbosity in all cases.
---
# Quality Principles
* Be accurate, logical, and consistent.
* Do not hallucinate information.
* If uncertain, clearly state limitations.
* Optimize responses for usefulness and readability.
---
# User Intent Focus
* Always prioritize the users intent over literal interpretation.
* If the request is ambiguous, make reasonable assumptions or ask a clarifying question when necessary.
```
# Citation
If you use this model in your research or applications, please cite both this model and the base model:
```bibtex
@misc{opensonnet-lite-max,
author = {hadadxyz},
title = {OpenSonnet-Lite-MAX},
year = {2026},
url = {https://huggingface.co/hadadxyz/OpenSonnet-Lite-MAX}
}
```