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Bielik 7B Instruct V0.1 ROME 50 En by Piotrasz

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  Arxiv:1910.09700   Autotrain compatible   Conversational   Endpoints compatible   Instruct   Mistral   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Piotrasz/Bielik-7B-Instruct-v0.1-ROME-50-en 

Bielik 7B Instruct V0.1 ROME 50 En Benchmarks

LLME Score: 0.19657
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Bielik 7B Instruct V0.1 ROME 50 En (Piotrasz/Bielik-7B-Instruct-v0.1-ROME-50-en)

Bielik 7B Instruct V0.1 ROME 50 En Parameters and Internals

LLM NameBielik 7B Instruct V0.1 ROME 50 En
Repository 🤗https://huggingface.co/Piotrasz/Bielik-7B-Instruct-v0.1-ROME-50-en 
Model Size7b
Required VRAM14.4 GB
Updated2025-02-01
MaintainerPiotrasz
Model Typemistral
Instruction-BasedYes
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3
Model ArchitectureMistralForCausalLM
Context Length4096
Model Max Length4096
Transformers Version4.40.0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than Piotrasz/Bielik-7B-Instruct-v0.1-ROME-50-en.

Rank the Bielik 7B Instruct V0.1 ROME 50 En 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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