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Boreas 10.7B Step2 by yhavinga

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  Arxiv:1910.09700   Arxiv:2312.15166   Autotrain compatible   Conversational   Endpoints compatible   Mistral   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/yhavinga/Boreas-10.7B-step2 

Boreas 10.7B Step2 Benchmarks

LLME Score: 0.18904
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Boreas 10.7B Step2 (yhavinga/Boreas-10.7B-step2)

Boreas 10.7B Step2 Parameters and Internals

Use Cases 
Considerations:
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model.
Additional Notes 
The model was continuously pretrained on a mix of Dutch and English for 20B tokens. It must be finetuned on an instruct or chat dataset to be useful.
Supported Languages 
NLP (Dutch, English)
Training Details 
Data Volume:
20B tokens
LLM NameBoreas 10.7B Step2
Repository 🤗https://huggingface.co/yhavinga/Boreas-10.7B-step2 
Model Size7b
Required VRAM21.4 GB
Updated2025-01-30
Maintaineryhavinga
Model Typemistral
Model Files  4.9 GB: 1-of-5   5.0 GB: 2-of-5   4.9 GB: 3-of-5   4.9 GB: 4-of-5   1.7 GB: 5-of-5
Model ArchitectureMistralForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.39.3
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than yhavinga/Boreas-10.7B-step2.

Rank the Boreas 10.7B Step2 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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Release v20241227
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