ajibawa-2023/Code-290k-6.7B-Instruct

Code-290k-6.7B-Instruct

This model is trained on DeepSeek-Coder-6.7B-Instruct. I have used my existing dataset Code-290k-ShareGPT for training purpose. It is trained on around 290000 set of codes. Along with Python, Java, JavaScript, GO, C++, Rust, Ruby, Sql, MySql, R, Julia, Haskell, etc. code with detailed explanation is used for training purpose. This model utilises Alpaca format. Besides code generation it will also give you explanation.

Training:

Entire dataset was trained on 4 x A100 80GB. For 3 epoch, training took 85 hours. DeepSeek-Coder codebase and DeepSpeed was used for training purpose.

This is a full fine tuned model.

Links for quantized models are given below.

Exllama

Exllama v2:Link

Extremely thankful to Bartowski for making Quantized version of the model.

Example Prompt:

This is a conversation with your helpful AI assistant. AI assistant can generate Code in various Programming Languages along with necessary explanation.

### Instruction:
{instruction}

### Response:

You can modify above Prompt as per your requirement. I have used Alpaca format.

I want to say special Thanks to the Open Source community for helping & guiding me to better understand the AI/Model development.

Thank you for your love & support.

Examples

1. Bayes Theorem - Python

2. Fermat's little theorem

3. The Arrhenius equation using R

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	36.64
AI2 Reasoning Challenge (25-Shot)	34.90
HellaSwag (10-Shot)	51.99
MMLU (5-Shot)	34.89
TruthfulQA (0-shot)	41.95
Winogrande (5-shot)	52.64
GSM8k (5-shot)	3.49