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Boreas 7B Chat by yhavinga

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  Autotrain compatible   Conversational   Dataset:euirim/goodwiki   Dataset:philschmid/flanv2   Dataset:teknium/openhermes-2.5 Dataset:yhavinga/mc4 nl cleane... Dataset:yhavinga/nedd wiki new...   Endpoints compatible   Finetuned   Mistral   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/yhavinga/Boreas-7B-chat 

Boreas 7B Chat Benchmarks

LLME Score: 0.18283
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Boreas 7B Chat (yhavinga/Boreas-7B-chat)

Boreas 7B Chat Parameters and Internals

Model Type 
text generation, chat model
Use Cases 
Areas:
research, commercial applications
Applications:
language translation, chatbots
Primary Use Cases:
natural language understanding, chat-oriented dialogue systems
Limitations:
model potential biases due to dataset composition
Additional Notes 
Boreas models focus on Dutch and English texts and are trained with the intent to preserve high-quality Dutch language capabilities.
Supported Languages 
languages_supported (Dutch, English), proficiency ()
Training Details 
Data Sources:
yhavinga/mc4_nl_cleaned, yhavinga/nedd_wiki_news, teknium/OpenHermes-2.5, euirim/goodwiki, philschmid/flanv2
Data Volume:
10 billion tokens
Context Length:
2048
Hardware Used:
TPU-v4-32
Model Architecture:
EasyDeL JAX framework
LLM NameBoreas 7B Chat
Repository 🤗https://huggingface.co/yhavinga/Boreas-7B-chat 
Model Size7b
Required VRAM14.4 GB
Updated2025-01-30
Maintaineryhavinga
Model Typemistral
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
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-7B-chat.

Rank the Boreas 7B Chat Capabilities

🆘 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! 🌟

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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