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sethuiyer/CodeCalc-Mistral-7B

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face
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CodeCalc-Mistral-7B

<p align="center"> <img src="https://huggingface.co/sethuiyer/CodeCalc-Mistral-7B/resolve/main/codecalc.webp" height="128px" alt="CodeCalc"> </p>

Configuration

The following YAML configuration was used to produce this model:

yaml

base_model: uukuguy/speechless-code-mistral-7b-v1.0
dtype: bfloat16
merge_method: ties
models:
- model: uukuguy/speechless-code-mistral-7b-v1.0
- model: upaya07/Arithmo2-Mistral-7B
  parameters:
    density:  [0.25, 0.35, 0.45, 0.35, 0.25]
    weight: [0.1, 0.25, 0.5, 0.25, 0.1]
parameters:
  int8_mask: true

Evaluation

TModelAverageARCHellaSwagMMLUTruthfulQAWinograndeGSM8K
๐Ÿ”sethuiyer/CodeCalc-Mistral-7B66.3361.9583.6462.7847.7978.363.53
๐Ÿ“‰uukuguy/speechless-code-mistral-7b-v1.063.661.1883.7763.447.978.3747.01

The merge appears to be successful, especially considering the substantial improvement in the GSM8K benchmark while maintaining comparable performance on other metrics.

Usage

Alpaca Instruction Format and Divine Intellect preset.

You are an intelligent programming assistant.

### Instruction:
Implement a linked list in C++

### Response:

Preset:

text
temperature: 1.31
top_p: 0.14
repetition_penalty: 1.17
top_k: 49

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

MetricValue
Avg.66.33
AI2 Reasoning Challenge (25-Shot)61.95
HellaSwag (10-Shot)83.64
MMLU (5-Shot)62.78
TruthfulQA (0-shot)47.79
Winogrande (5-shot)78.30
GSM8k (5-shot)63.53