README.md

---
library_name: transformers
tags:
- unsloth
license: cc-by-nc-2.0
base_model:
- unsloth/Meta-Llama-3.1-8B-bnb-4bit
---
# Model Card for LeoPARD 0.27  

<!--MODEL STILL IN DEVELOPMENT.-->  
**LeoPARD 0.27** is a fine-tuned version of **LLaMA 3.1 8B**, developed by **AxisSmart | Labs**. It incorporates **reasoning thinking** and **chain-of-thought (CoT) capabilities (beta)**, making it suitable for tasks requiring logical reasoning and step-by-step problem-solving.  

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## Model Details  

### Model Description  
This model is a fine-tuned version of **LLaMA 3.1 8B**, optimized for improved reasoning and chain-of-thought capabilities. It is designed to handle complex tasks that require logical thinking, structured reasoning, and multi-step problem-solving.  

- **Developed by:** AxisSmart | Labs  
- **Model type:** Fine-tuned language model  
- **Language(s) (NLP):** Primarily English (multilingual capabilities may vary)  
- **License:** [Creative Commons Attribution-NonCommercial 2.0  (CC BY-NC 2.0)]( https://creativecommons.org/licenses/by-nc/2.0/)  
- **Finetuned from model:** LLaMA 3.1 8B  

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### License Details  
The **CC BY-NC 4.0** license allows users to:  
- **Share:** Copy and redistribute the model in any medium or format.  
- **Adapt:** Remix, transform, and build upon the model for non-commercial purposes.  

Under the following terms:  
- **Attribution:** Users must give appropriate credit to **AxisSmart | Labs**, provide a link to the license, and indicate if changes were made.  
- **NonCommercial:** The model cannot be used for commercial purposes.  

For commercial use, explicit permission from **AxisSmart | Labs** is required.  

---

## Uses  

### Direct Use  
LeoPARD 0.27 can be used directly for tasks requiring reasoning and chain-of-thought capabilities, such as:  
- Logical problem-solving  
- Step-by-step reasoning tasks  
- Educational applications (e.g., math, science)  
- Decision support systems  

### Downstream Use [optional]  
The model can be fine-tuned further for specific applications, such as:  
- Custom reasoning pipelines  
- Domain-specific problem-solving (e.g., finance, healthcare)  
- Integration into larger AI systems  

### Out-of-Scope Use  
- Tasks requiring real-time, low-latency responses without proper optimization  
- Applications involving highly sensitive or unethical use cases  
- Tasks outside the scope of its reasoning and language capabilities  

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## Bias, Risks, and Limitations  
- **Bias:** The model may inherit biases present in the training data or the base LLaMA model.  
- **Risks:** Potential for incorrect or misleading reasoning outputs if not properly validated.  
- **Limitations:** The chain-of-thought capability is still in beta and may produce incomplete or suboptimal reasoning paths.  

### Recommendations  
Users should validate the model's outputs, especially for critical applications. Fine-tuning on domain-specific data may improve performance and reduce biases.  

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## How to Get Started with the Model  
Use the code below to load and use LeoPARD 0.27:  

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "model_name"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

input_text = "Explain the reasoning behind the solution to this problem: ..."
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```

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## Training Details  

### Training Data  
The model was fine-tuned on a curated dataset designed to enhance reasoning and chain-of-thought capabilities. The dataset includes:  
- Logical reasoning problems  
- Step-by-step solutions  
- General-purpose language data  

### Training Procedure  
- **Training time:** 6 hours
- **Training regime:** Mixed precision (bf16)
- **Hardware:** [Confidential]

#### Training Hyperparameters  
- **Learning rate:** 2e-4  
- **Batch size:** 2
- **Epochs:** 4

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## Evaluation  

Testing has not yet been conducted. Evaluation metrics and results will be added in future updates.

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## Model Card Authors  
AxisSmart | Labs  
VortexHunter(Alvin)

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## Model Card Contact  
Contact Comming Soon