library_name: transformers
license: apache-2.0
datasets:
- nickrosh/Evol-Instruct-Code-80k-v1
metrics:
- accuracy
pipeline_tag: text-generation
base_model: AIDC-ai-business/Luban-13B
Panda-Coder πΌ
Panda Coder is a state-of-the-art LLM capable of generating code on the NLP based Instructions
Model description
π€ Model Description: Panda-Coder is a state-of-the-art LLM, a fine-tuned model, specifically designed to generate code based on natural language instructions. It's the result of relentless innovation and meticulous fine-tuning, all to make coding easier and more accessible for everyone.
π Key Features:
π NLP-Based Coding: With Panda-Coder, you can transform your plain text instructions into functional code effortlessly. No need to grapple with syntax and semantics - it understands your language.
π― Precision and Efficiency: The model is tailored for accuracy, ensuring your code is not just functional but also efficient.
β¨ Unleash Creativity: Whether you're a novice or an expert coder, Panda-Coder is here to support your coding journey, offering creative solutions to your programming challenges.
π Evol Instruct Code: It's built on the robust Evol Instruct Code 80k-v1 dataset, guaranteeing top-notch code generation.
π’ What's Next?: We believe in continuous improvement and are excited to announce that in our next release, Panda-Coder will be enhanced with a custom dataset. This dataset will not only expand the language support but also include hardware programming languages like MATLAB, Embedded C, and Verilog. π§°π‘
Get in Touch
You can schedule 1:1 meeting with our DevRel & Community Team to get started with AI Planet Open Source LLMs and GenAI Stack. Schedule the call here: https://calendly.com/jaintarun
Stay tuned for more updates and be a part of the coding evolution. Join us on this exciting journey as we make AI accessible to all at AI Planet!
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
Citation
@misc {lucifertrj,
author = { {Tarun Jain} },
title = { Panda Coder-13B by AI Planet},
year = 2023,
url = { https://huggingface.co/aiplanet/panda-coder-13B },
publisher = { Hugging Face }
}