Code: https://github.com/uukuguy/speechless
Use the following dataset to fine-tune mistralai/Mistral-7B-v0.2 in order to improve the model's reasoning and planning abilities.
Total 201,981 samples.
This model accepts the Alpaca instruction format.
For example:
You are an intelligent programming assistant.
### Instruction:
Implement a linked list in C++
### Response:
| Metric | Value |
|---|---|
| humaneval-python |
Big Code Models Leaderboard](https://huggingface.co/spaces/bigcode/bigcode-models-leaderboard)
CodeLlama-34B-Python: 53.29
CodeLlama-34B-Instruct: 50.79
CodeLlama-13B-Instruct: 50.6
CodeLlama-34B: 45.11
CodeLlama-13B-Python: 42.89
CodeLlama-13B: 35.07
| Metric | Value |
|---|---|
| ARC | 58.79 |
| HellaSwag | 81.89 |
| MMLU | 61.27 |
| TruthfulQA | 49.85 |
| Winoground | 78.22 |
| GSM8K | 56.33 |
| Average | 64.39 |
3 commits
Code: https://github.com/uukuguy/speechless
Use the following dataset to fine-tune mistralai/Mistral-7B-v0.2 in order to improve the model's reasoning and planning abilities.
Total 201,981 samples.
This model accepts the Alpaca instruction format.
For example:
You are an intelligent programming assistant.
### Instruction:
Implement a linked list in C++
### Response:
| Metric | Value |
|---|---|
| humaneval-python |
Big Code Models Leaderboard](https://huggingface.co/spaces/bigcode/bigcode-models-leaderboard)
CodeLlama-34B-Python: 53.29
CodeLlama-34B-Instruct: 50.79
CodeLlama-13B-Instruct: 50.6
CodeLlama-34B: 45.11
CodeLlama-13B-Python: 42.89
CodeLlama-13B: 35.07
| Metric | Value |
|---|---|
| ARC | 58.79 |
| HellaSwag | 81.89 |
| MMLU | 61.27 |
| TruthfulQA | 49.85 |
| Winoground | 78.22 |
| GSM8K | 56.33 |
| Average | 64.39 |
3 commits