|
--- |
|
title: README |
|
emoji: 🐢 |
|
colorFrom: purple |
|
colorTo: pink |
|
sdk: static |
|
pinned: false |
|
--- |
|
|
|
## Panda Villa Tech Limited |
|
|
|
**Long-term Focus:** |
|
|
|
- Our company is dedicated to long-term specialization in **synthetic data**, **metaphysics**, and **psychology LLM**, exploring how these fields can intersect with artificial intelligence. |
|
|
|
**Product:** DataTager |
|
|
|
**Website:** [DataTager.com](https://DataTager.com/) |
|
|
|
- **Description:** DataTager is a tool designed to evaluate and generate the training data needed for large language models. We believe it's more important for individuals and enterprises to fine-tune large models easily and create models tailored to their specific business needs, rather than just choosing models with the highest benchmarks. |
|
|
|
**Philosophy:** |
|
|
|
- We published a paper titled "AnyTaskTune," advocating that task-specific fine-tuning based on real-world scenarios is crucial. This approach is more significant than using universally high-scoring models. |
|
|
|
**Resources:** |
|
|
|
- We have open-sourced various subtask datasets across multiple domains to support the community. These resources are available on our website for anyone interested in specific task fine-tuning. |
|
|
|
Explore more on how to fine-tune your tasks efficiently with our resources at [DataTager.com](https://DataTager.com/). |
|
|
|
|
|
|
