---
base_model: mistralai/Ministral-8B-Instruct-2410
tags:
- text-generation-inference
- transformers
- unsloth
- mistral
- trl
license: other
license_name: mrl
license_link: LICENSE
language:
- en
---
![Header](https://raw.githubusercontent.com/Aayan-Mishra/Images/refs/heads/main/Ava.png)

# Ava 1.0

**Ava 1.0** is an advanced AI model fine-tuned on the Mistral architecture, featuring 8 billion parameters. Designed to be smarter, stronger, and swifter, Ava 1.0 excels in tasks requiring comprehension, reasoning, and language generation, making it a versatile solution for various applications.

---

## Key Features

1. **Compact Yet Powerful**:
   - With 8 billion parameters, Ava 1.0 strikes a balance between computational efficiency and performance.
   
2. **Enhanced Reasoning Capabilities**:
   - Fine-tuned to provide better logical deductions and insightful responses across multiple domains.

3. **Optimized for Efficiency**:
   - Faster inference and reduced resource requirements compared to larger models.

---

## Use Cases

- **Conversational AI**: Natural and context-aware dialogue generation.
- **Content Creation**: Generate articles, summaries, and creative writing.
- **Educational Tools**: Assist with problem-solving and explanations.
- **Data Analysis**: Derive insights from structured and unstructured data.

---

## Technical Specifications

- **Model Architecture**: Ministral-8B-Instruct-2410
- **Parameter Count**: 8 Billion
- **Training Dataset**: A curated dataset spanning diverse fields, including literature, science, technology, and general knowledge.
- **Framework**: Hugging Face Transformers

---

## Usage

To use Ava 1.0, integrate it into your Python environment with Hugging Face's `transformers` library:

```python
# Use a pipeline as a high-level helper
from transformers import pipeline

messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe = pipeline("text-generation", model="Spestly/Ava-1.0-8B")
pipe(messages)  

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Spestly/Ava-1.0-8B")
model = AutoModelForCausalLM.from_pretrained("Spestly/Ava-1.0-8B")
```

---

## Performance Benchmarks

| Metric               | Value       |
|----------------------|-------------|
| Inference Speed      | **2x faster** than Ava 1.0 (12B model) |
| Accuracy (Benchmarks)| **90%** on standard NLP tasks         |
| Resource Utilization | Reduced memory footprint by **30%**   |

---

## Future Plans

- Continued optimization for domain-specific applications.
- Expanding the model's adaptability and generalization capabilities.

---

## Contributing

We welcome contributions and feedback to improve Ava 1.0. If you'd like to get involved, please reach out or submit a pull request.

---

## License

This model is licensed under Mistral Research License. Please review the license terms before usage.