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EmbeddedLLM/Mistral-7B-Merge-14-v0.3
Mistral-7B-Merge-14-v0.3 is a text generation model from EmbeddedLLM. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
Check out our v0.4 model which is based on this and achieves better average score of 71.19 versus 69.66.
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From the Hugging Face model README
Check out our v0.4 model which is based on this and achieves better average score of 71.19 versus 69.66.
This is an update to EmbeddedLLM/Mistral-7B-Merge-14-v0.2 that removes potentially TruthfulQA-contaminated models and non-commercially licensed models:
This is an experiment to test merging 14 models using DARE TIES 🦙
The result is a base model that performs quite well but may need some further chat fine-tuning.
The 14 models are as follows:
| v0.3 | v0.4 | |
|---|---|---|
| Average | 69.66 | 71.19 |
| ARC | 65.96 | 66.81 |
| HellaSwag | 85.29 | 86.15 |
| MMLU | 64.35 | 65.10 |
| TruthfulQA | 57.80 | 58.25 |
| Winogrande | 78.30 | 80.03 |
| GSM8K | 66.26 | 70.81 |
We tried ChatML and Llama-2 chat template, but feel free to try other templates.
The merge config file for this model is here:
models:
- model: mistralai/Mistral-7B-v0.1
# no parameters necessary for base model
- model: ehartford/dolphin-2.2.1-mistral-7b
parameters:
weight: 0.08
density: 0.4
- model: SciPhi/SciPhi-Mistral-7B-32k
parameters:
weight: 0.08
density: 0.4
- model: ehartford/samantha-1.2-mistral-7b
parameters:
weight: 0.08
density: 0.4
- model: Arc53/docsgpt-7b-mistral
parameters:
weight: 0.08
density: 0.4
- model: HuggingFaceH4/zephyr-7b-beta
parameters:
weight: 0.08
density: 0.4
- model: meta-math/MetaMath-Mistral-7B
parameters:
weight: 0.08
density: 0.4
- model: Open-Orca/Mistral-7B-OpenOrca
parameters:
weight: 0.08
density: 0.4
- model: openchat/openchat-3.5-1210
parameters:
weight: 0.08
density: 0.4
- model: beowolx/MistralHermes-CodePro-7B-v1
parameters:
weight: 0.08
density: 0.4
- model: TIGER-Lab/MAmmoTH-7B-Mistral
parameters:
weight: 0.08
density: 0.4
- model: teknium/OpenHermes-2.5-Mistral-7B
parameters:
weight: 0.08
density: 0.4
- model: Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp
parameters:
weight: 0.08
density: 0.4
- model: mlabonne/NeuralHermes-2.5-Mistral-7B
parameters:
weight: 0.08
density: 0.4
- model: mistralai/Mistral-7B-Instruct-v0.2
parameters:
weight: 0.08
density: 0.5
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
int8_mask: true
dtype: bfloat16