--- 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 🐼 ![1*E4V6iZPaeE6iTZjAleCt3Q.webp](https://cdn-uploads.huggingface.co/production/uploads/630f3058236215d0b7078806/q4k9YbKDW3eypKmOJio5j.webp) 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 ```python 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 ```bash 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](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 } } ```