Merged Model Autotrain compatible Base model:mlabonne/monarch-7b Base model:vanillaovo/supermar... Endpoints compatible Mistral Mlabonne/monarch-7b Model-index Region:us Safetensors Sharded Tensorflow Vanillaovo/supermario v4
NeuralMarioMonarch 7B Slerp Benchmarks
ARC: 73.81 vs 96.7 (so35)-23.7%
HellaSwag: 89.04 vs 95.3 (gpt4)-6.6%
MMLU: 64.61 vs 88.3 (so35)-26.8%
TruthfulQA: 74.97 vs 59 (gpt4)27.1%
WinoGrande: 85 vs 87.5 (gpt4)-2.9%
GSM8K: 69.22 vs 96.4 (so35)-28.2%
LLME Score: 0.19604
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
What is the LLM Explorer Rank (Score)
NeuralMarioMonarch 7B Slerp Parameters and Internals
| LLM Name | NeuralMarioMonarch 7B Slerp |
| Repository 🤗 | https://huggingface.co/Kukedlc/NeuralMarioMonarch-7B-slerp |
| Base Model(s) | |
| Merged Model | Yes |
| Model Size | 7b |
| Required VRAM | 14.4 GB |
| Updated | 2024-10-18 |
| Maintainer | Kukedlc |
| Model Type | mistral |
| Model Files | |
| Model Architecture | MistralForCausalLM |
| License | apache-2.0 |
| Context Length | 32768 |
| Model Max Length | 32768 |
| Transformers Version | 4.37.2 |
| Tokenizer Class | LlamaTokenizer |
| Vocabulary Size | 32000 |
| Torch Data Type | float16 |
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| ...Nemo Instruct 2407 Abliterated | 1000K / 24.5 GB | 2175 | 6 |
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| MegaBeam Mistral 7B 300K | 282K / 14.4 GB | 1061 | 15 |
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| Astral 256K 7B V2 | 250K / 14.4 GB | 8 | 0 |
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| Boptruth Agatha 7B | 128K / 14.4 GB | 608 | 0 |
| Buddhi 128K Chat 7B | 128K / 14.4 GB | 1301 | 15 |
| Test001 | 128K / 14.5 GB | 5 | 0 |
Note: green Score (e.g. "73.2") means that the model is better than Kukedlc/NeuralMarioMonarch-7B-slerp .
Rank the NeuralMarioMonarch 7B Slerp Capabilities
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v2024072803