library_name: transformers
license: apache-2.0
datasets:
- TokenBender/code_instructions_122k_alpaca_style
metrics:
- accuracy
pipeline_tag: text-generation
base_model: codellama/CodeLlama-13b-Instruct-hf
Panda-Coder 🐼
Panda Coder is a state-of-the-art LLM capable of generating code on the NLP based Instructions
Model description
🤖 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.
Inference
import torch
import transformers
from transformers import AutoModelForCausalLM, AutoTokenizer, TrainingArguments,BitsAndBytesConfig
prompt = f"""### Instruction:
Below is an instruction that describes a task. Write a response that appropriately completes the request.
Write a Python quickstart script to get started with TensorFlow
### Input:
### Response:
"""
input_ids = tokenizer(prompt, return_tensors="pt", truncation=True).input_ids.cuda()
outputs = base_model.generate(input_ids=input_ids, max_new_tokens=512, do_sample=True, top_p=0.9,temperature=0.1,repetition_penalty=1.1)
print(f"Output:\n{tokenizer.batch_decode(outputs.detach().cpu().numpy(), skip_special_tokens=True)[0][len(prompt):]}")
Output
Output:
import tensorflow as tf
# Create a constant tensor
hello_constant = tf.constant('Hello, World!')
# Print the value of the constant
print(hello_constant)
🔗 Key Features:
🌟 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.
🎯 Precision and Efficiency: The model is tailored for accuracy, ensuring your code is not just functional but also efficient.
✨ 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.
📚 Evol Instruct Code: It's built on the robust Evol Instruct Code 80k-v1 dataset, guaranteeing top-notch code generation.
📢 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. 🧰💡
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 }
}