license, base_model, library_name, tags, model-index

license	base_model	library_name	tags	model-index
apache-2.0	cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser Locutusque/Hyperion-1.5-Mistral-7B ibm/merlinite-7b	transformers	mergekit merge code	name results Magic-Dolphin-7b task dataset metrics source type name text-generation Text Generation name type config split args AI2 Reasoning Challenge (25-Shot) ai2_arc ARC-Challenge test num_few_shot 25 type value name acc_norm 65.78 normalized accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=InferenceIllusionist/Magic-Dolphin-7b Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type split args HellaSwag (10-Shot) hellaswag validation num_few_shot 10 type value name acc_norm 85.61 normalized accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=InferenceIllusionist/Magic-Dolphin-7b Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args MMLU (5-Shot) cais/mmlu all test num_few_shot 5 type value name acc 64.64 accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=InferenceIllusionist/Magic-Dolphin-7b Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args TruthfulQA (0-shot) truthful_qa multiple_choice validation num_few_shot 0 type value mc2 58.01 url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=InferenceIllusionist/Magic-Dolphin-7b Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args Winogrande (5-shot) winogrande winogrande_xl validation num_few_shot 5 type value name acc 79.64 accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=InferenceIllusionist/Magic-Dolphin-7b Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args GSM8k (5-shot) gsm8k main test num_few_shot 5 type value name acc 51.18 accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=InferenceIllusionist/Magic-Dolphin-7b Open LLM Leaderboard

Magic-Dolphin-7b

The follow-up to this model has been released, check out the updated benchmarks here for Excalibur-7b

A full suite of GGUF quantizations can be found here, courtesy of RichardErkhov

A linear merge of:

• cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser
• Locutusque/Hyperion-1.5-Mistral-7B
• ibm/merlinite-7b

These three models showed excellent acumen in technical topics so I wanted to see how they would behave together in a merge. Several different ratios were tested before this release, in the end a higher weighting for merlinite-7b helped smooth out some edges. This model is a test of how LAB tuning is impacted by merges with models leveraging DPO.

Benchmark Performance

Name	Avg.	ARC	HellaSwag	MMLU	TruthfulQA	Winogrande	GSM8K
Magic-Dolphin-7b	67.48	65.78	85.61	64.64	58.01	79.64	51.18
dolphin-2.6-mistral-7b-dpo-laser	67.28	66.3	85.73	63.16	61.71	79.16	47.61
merlinite-7b	64	63.65	84.52	64.91	50.15	79.72	41.09
Hyperion-1.5-Mistral-7B	61.43	60.49	83.64	63.57	41.78	78.61	40.49

This was my first experiment with merging models so any feedback is greatly appreciated.

Uses Alpaca template.

Sample Question

Merge Details

Merge Method

This model was merged using the linear merge method.

Models Merged

The following models were included in the merge:

• cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser
• Locutusque/Hyperion-1.5-Mistral-7B
• ibm/merlinite-7b

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: models/dolphin-2.6-mistral-7b-dpo-laser
    parameters:
      weight: 1.0
  - model: models/Hyperion-1.5-Mistral-7B
    parameters:
      weight: 0.3
  - model: models/merlinite-7b
    parameters:
      weight: 0.5
merge_method: linear
dtype: float16

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	67.48
AI2 Reasoning Challenge (25-Shot)	65.78
HellaSwag (10-Shot)	85.61
MMLU (5-Shot)	64.64
TruthfulQA (0-shot)	58.01
Winogrande (5-shot)	79.64
GSM8k (5-shot)	51.18