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---
base_model: unsloth/qwen2.5-coder-1.5b-instruct
tags:
- text-generation-inference
- transformers
- unsloth
- qwen2
- trl
license: apache-2.0
language:
- en
datasets:
- Daemontatox/math_conv
library_name: transformers
model-index:
- name: Zirel_1.5
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: wis-k/instruction-following-eval
split: train
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 41.68
name: averaged accuracy
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FZirel_1.5
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: SaylorTwift/bbh
split: test
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 15.08
name: normalized accuracy
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FZirel_1.5
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: lighteval/MATH-Hard
split: test
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 11.33
name: exact match
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FZirel_1.5
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
split: train
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 1.34
name: acc_norm
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FZirel_1.5
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MuSR (0-shot)
type: TAUR-Lab/MuSR
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 3.33
name: acc_norm
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FZirel_1.5
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU-PRO (5-shot)
type: TIGER-Lab/MMLU-Pro
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 12.71
name: accuracy
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FZirel_1.5
name: Open LLM Leaderboard
---
# Zireal 1.5 - Fast Reasoning Model
**Developed by:** Daemontatox
**Finetuned from:** [unsloth/qwen2.5-coder-1.5b-instruct](https://huggingface.co./unsloth/qwen2.5-coder-1.5b-instruct)
**License:** Apache 2.0
## Overview
**Zireal 1.5** is a **fast, efficient reasoning model** designed for structured problem-solving and mathematical inference. It has been fine-tuned using **GRPO (General Reinforcement Policy Optimization)** on **24,000 high-quality mathematical examples**, making it highly effective for step-by-step reasoning and logic-based tasks.
## Features
- **Optimized for fast, structured reasoning** with minimal computational overhead.
- **GRPO-trained** for superior decision-making in mathematical contexts.
- **Lightweight yet highly capable**, leveraging Qwen2.5's instruction-tuned efficiency.
- **Ideal for logic, algebra, arithmetic, and structured problem-solving.**
## Usage
You can load **Zireal 1.5** using `transformers`:
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "Daemontatox/Zireal-1.5" # Replace with actual model name
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
inputs = tokenizer("Solve: 3x - 7 = 11", return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=50)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```
## Intended Use
- **Mathematical reasoning** (algebra, arithmetic, logic-based problems).
- **Step-by-step structured problem-solving** for computational tasks.
- **Lightweight inference** for fast, efficient reasoning applications.
## Limitations
- Primarily designed for structured reasoning rather than open-ended text generation.
- Best suited for logic and mathematics rather than creative or conversational AI.
## Acknowledgments
**Zireal 1.5** is part of the **Zireal** model series, focusing on efficient and necessary reasoning. It is built on **Qwen2.5** and optimized using **Unsloth** for high-performance inference.
---
🔗 **[Hugging Face Model Card](https://huggingface.co./Daemontatox/Zireal-1.5)** (Replace with actual link)
📜 **License:** Apache 2.0
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co./datasets/open-llm-leaderboard/Daemontatox__Zirel_1.5-details)!
Summarized results can be found [here](https://huggingface.co./datasets/open-llm-leaderboard/contents/viewer/default/train?q=Daemontatox%2FZirel_1.5&sort[column]=Average%20%E2%AC%86%EF%B8%8F&sort[direction]=desc)!
| Metric |Value (%)|
|-------------------|--------:|
|**Average** | 14.24|
|IFEval (0-Shot) | 41.68|
|BBH (3-Shot) | 15.08|
|MATH Lvl 5 (4-Shot)| 11.33|
|GPQA (0-shot) | 1.34|
|MuSR (0-shot) | 3.33|
|MMLU-PRO (5-shot) | 12.71|
|