metadata
license: apache-2.0
base_model:
- meta-llama/Llama-3.1-8B-Instruct
pipeline_tag: text-generation
library_name: transformers
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.
GGUF Files
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.