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Yam Jom 7B Dare by mayacinka

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  Merged Model   Autotrain compatible Base model:eren23/ogno-monarch... Base model:yam-peleg/experimen...   Endpoints compatible Eren23/ogno-monarch-jaskier-me...   Mistral   Region:us   Safetensors   Sharded   Tensorflow   Yam-peleg/experiment26-7b

Yam Jom 7B Dare Benchmarks

ARC: 73.38 vs 96.7 (so35)-24.1%
HellaSwag: 89.14 vs 95.3 (gpt4)-6.5%
MMLU: 64.38 vs 88.3 (so35)-27.1%
TruthfulQA: 78.04 vs 59 (gpt4)32.3%
WinoGrande: 84.85 vs 87.5 (gpt4)-3%
GSM8K: 69.83 vs 96.4 (so35)-27.6%
LLME Score: 0.20039
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Yam Jom 7B Dare Parameters and Internals

LLM NameYam Jom 7B Dare
Repository 🤗https://huggingface.co/mayacinka/yam-jom-7B-dare 
Base Model(s)  ...askier Merge 7B OH PREF DPO V2   Experiment26 7B   eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO-v2   yam-peleg/Experiment26-7B
Merged ModelYes
Model Size7b
Required VRAM42.8 GB
Updated2024-10-08
Maintainermayacinka
Model Typemistral
Model Files  9.9 GB: 1-of-2   9.9 GB: 1-of-3   4.5 GB: 2-of-2   9.9 GB: 2-of-3   8.6 GB: 3-of-3
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.38.1
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32000
Torch Data Typebfloat16
Yam Jom 7B Dare (mayacinka/yam-jom-7B-dare)

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Note: green Score (e.g. "73.2") means that the model is better than mayacinka/yam-jom-7B-dare.

Rank the Yam Jom 7B Dare Capabilities

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Release v2024072803
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