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 |