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ML MS Etheris 123B by Steelskull

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ML MS Etheris 123B is an open-source language model by Steelskull. Features: 123b LLM, VRAM: 226.4GB, Context: 32K, Instruction-Based, LLM Explorer Score: 0.16.

  Autotrain compatible Base model:anthracite-org/magn... Base model:merge:anthracite-or... Base model:merge:migtissera/te... Base model:merge:neversleep/lu... Base model:merge:sillytilly/mi... Base model:merge:thedrummer/be... Base model:migtissera/tess-3-m... Base model:neversleep/lumimaid... Base model:sillytilly/mistral-... Base model:thedrummer/behemoth...   Endpoints compatible   Instruct   Merge   Mergekit   Mistral   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Steelskull/ML-MS-Etheris-123B 

ML MS Etheris 123B Benchmarks

LLME Score: 0.15532
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
ML MS Etheris 123B (Steelskull/ML-MS-Etheris-123B)
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ML MS Etheris 123B Parameters and Internals

Additional Notes 
The model combines the storytelling capabilities of multiple models maintaining intelligence.
Training Details 
Methodology:
Merged using Model Soup with DELLA as a special methodology.
Input Output 
Input Format:
Use Mistral, ChatML, or Meth Format
LLM NameML MS Etheris 123B
Repository 🤗https://huggingface.co/Steelskull/ML-MS-Etheris-123B 
Base Model(s)  Tess 3 Mistral Large 2 123B   Behemoth 123B V1   Mistral Large Instruct 2407   NeverSleep/Lumimaid-v0.2-123B   Magnum V2 123B   migtissera/Tess-3-Mistral-Large-2-123B   TheDrummer/Behemoth-123B-v1   SillyTilly/Mistral-Large-Instruct-2407   NeverSleep/Lumimaid-v0.2-123B   anthracite-org/magnum-v2-123b
Model Size123b
Required VRAM226.4 GB
Updated2025-01-17
MaintainerSteelskull
Model Typemistral
Instruction-BasedYes
Model Files  4.4 GB: 1-of-51   4.9 GB: 2-of-51   4.8 GB: 3-of-51   4.8 GB: 4-of-51   4.8 GB: 5-of-51   4.9 GB: 6-of-51   4.8 GB: 7-of-51   4.8 GB: 8-of-51   4.8 GB: 9-of-51   4.9 GB: 10-of-51   4.8 GB: 11-of-51   4.8 GB: 12-of-51   4.8 GB: 13-of-51   4.9 GB: 14-of-51   4.8 GB: 15-of-51   4.8 GB: 16-of-51   4.8 GB: 17-of-51   4.9 GB: 18-of-51   4.8 GB: 19-of-51   4.8 GB: 20-of-51   4.8 GB: 21-of-51   4.9 GB: 22-of-51   4.8 GB: 23-of-51   4.8 GB: 24-of-51   4.8 GB: 25-of-51   4.9 GB: 26-of-51   4.8 GB: 27-of-51   4.8 GB: 28-of-51   4.8 GB: 29-of-51   4.9 GB: 30-of-51   4.8 GB: 31-of-51   4.8 GB: 32-of-51   4.8 GB: 33-of-51   4.9 GB: 34-of-51   4.8 GB: 35-of-51   4.8 GB: 36-of-51   4.8 GB: 37-of-51   4.9 GB: 38-of-51   4.8 GB: 39-of-51   4.8 GB: 40-of-51   4.8 GB: 41-of-51   4.9 GB: 42-of-51   4.8 GB: 43-of-51   4.8 GB: 44-of-51   4.8 GB: 45-of-51   4.9 GB: 46-of-51   4.8 GB: 47-of-51
Model ArchitectureMistralForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.44.1
Vocabulary Size32768
Torch Data Typebfloat16

Best Alternatives to ML MS Etheris 123B

Best Alternatives
Context / RAM
Downloads
Likes
Behemoth X 123B V2128K / 217.2 GB24330
Behemoth ReduX 123B V1128K / 217.2 GB3213
Behemoth R1 123B V2128K / 226.4 GB3227
ML2 123B Magnum Diamond128K / 212.4 GB711
Gigaberg Mistral Large 123B128K / 222 GB62
Cakrawala 123B128K / 222 GB264
Behemoth 123B V2128K / 221.6 GB5210
Behemoth 123B V1128K / 221.6 GB7244
Magnum V4 123B128K / 222 GB9632
Magnum V2 123B128K / 207.6 GB5664
Note: green Score (e.g. "73.2") means that the model is better than Steelskull/ML-MS-Etheris-123B.

Rank the ML MS Etheris 123B Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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