BerryBase by jeiku

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  Merged Model   Autotrain compatible Base model:maywell/qwen2-7b-mu... Base model:weyaxi/einstein-v7-...   Conversational   Endpoints compatible Maywell/qwen2-7b-multilingual-...   Qwen2   Region:us   Safetensors   Sharded   Tensorflow   Weyaxi/einstein-v7-qwen2-7b
Model Card on HF ๐Ÿค—: https://huggingface.co/jeiku/BerryBase 

BerryBase Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
BerryBase (jeiku/BerryBase)

BerryBase Parameters and Internals

Model Type 
merge
Training Details 
Methodology:
Merge using LazyMergekit
Input Output 
Input Format:
structured prompts with message role content format
Accepted Modalities:
text
Output Format:
text
LLM NameBerryBase
Repository ๐Ÿค—https://huggingface.co/jeiku/BerryBase 
Base Model(s)  Qwen2 7B Multilingual RP   Einstein V7 Qwen2 7B   maywell/Qwen2-7B-Multilingual-RP   Weyaxi/Einstein-v7-Qwen2-7B
Merged ModelYes
Model Size7b
Required VRAM15.2 GB
Updated2025-01-17
Maintainerjeiku
Model Typeqwen2
Model Files  5.0 GB: 1-of-4   4.9 GB: 2-of-4   5.0 GB: 3-of-4   0.3 GB: 4-of-4
Model ArchitectureQwen2ForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.42.3
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than jeiku/BerryBase.

Rank the BerryBase Capabilities

๐Ÿ†˜ Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! ๐ŸŒŸ

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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227