SeaLLMs V3.1.5B by SeaLLMs

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  Arxiv:2009.03300   Arxiv:2306.05179   Arxiv:2407.19672   Autotrain compatible   Conversational   En   Endpoints compatible   Id   Jv   Ms   Multilingual   Qwen2   Region:us   Safetensors   Sea   Sharded   Ta   Tensorflow   Th   Tl   Vi   Zh
Model Card on HF ๐Ÿค—: https://huggingface.co/SeaLLMs/SeaLLMs-v3-1.5B 

SeaLLMs V3.1.5B Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
SeaLLMs V3.1.5B (SeaLLMs/SeaLLMs-v3-1.5B)

SeaLLMs V3.1.5B Parameters and Internals

Use Cases 
Areas:
Southeast Asian languages
Primary Use Cases:
Multilingual language handling, Translation, Instruction-following, Mathematical reasoning, World knowledge tasks
Additional Notes 
Ensures safety in usage with significantly reduced instances of hallucination and sensitivity to local contexts.
Supported Languages 
en (English), zh (Chinese), id (Indonesian), vi (Vietnamese), th (Thai), ms (Malay), tl (Tagalog), ta (Tamil), jv (Javanese)
LLM NameSeaLLMs V3.1.5B
Repository ๐Ÿค—https://huggingface.co/SeaLLMs/SeaLLMs-v3-1.5B 
Model Size1.5b
Required VRAM6.2 GB
Updated2024-12-21
MaintainerSeaLLMs
Model Typeqwen2
Model Files  5.0 GB: 1-of-2   1.2 GB: 2-of-2
Supported Languagesen zh id vi th ms tl ta jv
Model ArchitectureQwen2ForCausalLM
Licenseother
Context Length131072
Model Max Length131072
Transformers Version4.38.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typefloat32
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than SeaLLMs/SeaLLMs-v3-1.5B.

Rank the SeaLLMs V3.1.5B 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241217