Code-Mistral-7B

This Model is trained on refined version of my dataset Code-290k-ShareGPT.

Besides this it is trained on following datasets:

The idea was to check how this Model will perform with both Code & Maths datasets. This model is very good with Coding. Maths is still hit & miss but you can test out this model.

This Model is trained on massive datasets so the results are very good. I have used ChatML prompt format.

Kindly note this is qLoRA version, a rare exception.

GGUF & Exllama

GGUF: Link

Exllama v2: Link

Special Thanks to Bartowski for quantizing this model.

Training:

Entire dataset was trained on 4 x A100 80GB. For 3 epoch, training took almost 33 Hours. Axolotl codebase was used for training purpose. Entire data is trained on Mistral.

Example Prompt: This model uses ChatML prompt format.

<|im_start|>system
You are a helpful AI assistant.<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

You can modify above Prompt as per your requirement.

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.

Example Output

C++

Error Resolving

Matrices

Machine Learning

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	69.97
AI2 Reasoning Challenge (25-Shot)	64.59
HellaSwag (10-Shot)	85.29
MMLU (5-Shot)	65.00
TruthfulQA (0-shot)	54.64
Winogrande (5-shot)	82.24
GSM8k (5-shot)	68.08

ajibawa-2023
/

Code-Mistral-7B

Open LLM Leaderboard Evaluation Results

Model tree for ajibawa-2023/Code-Mistral-7B

Datasets used to train ajibawa-2023/Code-Mistral-7B

Spaces using ajibawa-2023/Code-Mistral-7B 6

Evaluation results