README.md

---
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
---

<p align="center" style="font-size:34px;"><b>Panda-Coder 🐼</b></p>

![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 }
}
 ```