DavidBrowne17/LlamaThink-8B-instruct-GGUF

license: apache-2.0 base_model: - meta-llama/Llama-3.1-8B-Instruct

LlamaThink-8b-instruct

LlamaThink-8b-instruct is an instruction-tuned language model built on the LLaMA-3 architecture. It is optimized for generating thoughtful, structured responses using a unique dual-section output format.

Model Details

• Architecture: LLaMA-3
• Size: 8 billion parameters
• License: Apache 2.0

Usage

System Prompt

To ensure the model generates responses in the intended format, use the following system prompt:

Respond in the following format:
<thinking>
...
</thinking>
<answer>
...
</answer>

Example Input

What are the benefits of using LlamaThink-8b-instruct for AI research?

Example Output

<thinking>
LlamaThink-8b-instruct is built on the robust LLaMA-3 architecture, which offers enhanced performance and scalability. Its instruction-tuning ensures it understands complex prompts and provides structured responses. This makes it ideal for research applications where clarity and precision are essential.
</thinking>
<answer>
Using LlamaThink-8b-instruct for AI research provides benefits such as improved contextual understanding, consistent response formatting, and adaptability to various domains. Its open-source Apache 2.0 license also encourages innovation and collaboration.
</answer>

Installation

You can load the model directly from Hugging Face:

from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "DavidBrowne17/LlamaThink-8B-instruct"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

Citation

If you use LlamaThink-8b-instruct in your research or applications, please cite it as follows:

@misc{llamathink2025,
  author = {David Browne},
  title = {LlamaThink-8b-instruct},
  year = {2025},
  publisher = {Hugging Face},
  howpublished = {\url{https://huggingface.co/DavidBrowne17/LlamaThink-8B-instruct}},
  license = {Apache 2.0}
}

License

LlamaThink-8b-instruct is released under the Apache License 2.0.

Contact

For questions or contributions, reach out via Hugging Face or GitHub.