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Llama 3 Taiwan 8B Instruct by yentinglin

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Llama 3 Taiwan 8B Instruct is an open-source language model by yentinglin. Features: 70b LLM, VRAM: 16.1GB, Context: 8K, License: llama3, Instruction-Based, LLM Explorer Score: 0.18.

  Arxiv:2311.17487   Arxiv:2403.20180   Autotrain compatible Base model:finetune:meta-llama... Base model:meta-llama/meta-lla...   Conversational   En   Endpoints compatible   Instruct   Llama   Region:us   Safetensors   Sharded   Tensorflow   Zh   Zhtw
Model Card on HF 🤗: https://huggingface.co/yentinglin/Llama-3-Taiwan-8B-Instruct 

Llama 3 Taiwan 8B Instruct Benchmarks

LLME Score: 0.18368
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llama 3 Taiwan 8B Instruct (yentinglin/Llama-3-Taiwan-8B-Instruct)
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Llama 3 Taiwan 8B Instruct Parameters and Internals

Model Type 
text-generation, multi-turn dialogue, language understanding
Use Cases 
Areas:
Traditional Mandarin NLP tasks, English NLP tasks
Applications:
Multi-turn dialogue, RAG (Retrieval-Augmented Generation), Language understanding, Entity recognition, Function calling
Primary Use Cases:
NLP tasks, Legal, Manufacturing, Medical, Electronics
Additional Notes 
The compute and data for training were generously sponsored by local organizations.
Supported Languages 
Traditional Mandarin (High), English (High)
Training Details 
Data Sources:
High-quality Traditional Mandarin, English corpus, Legal, Manufacturing, Medical, Electronics domains
Methodology:
Finetuned using NVIDIA NeMo Framework
Context Length:
8000
Hardware Used:
NVIDIA DGX H100
Model Architecture:
Llama-3 architecture
Input Output 
Accepted Modalities:
text
Performance Tips:
Set system message for optimal results.
Release Notes 
Version:
rc1
Notes:
Initial release of Llama-3-Taiwan-70B-Instruct-rc1 for public testing.
LLM NameLlama 3 Taiwan 8B Instruct
Repository 🤗https://huggingface.co/yentinglin/Llama-3-Taiwan-8B-Instruct 
Base Model(s)  Meta Llama 3 70B   meta-llama/Meta-Llama-3-70B
Model Size70b
Required VRAM16.1 GB
Updated2025-09-23
Maintaineryentinglin
Model Typellama
Instruction-BasedYes
Model Files  5.0 GB: 1-of-4   5.0 GB: 2-of-4   4.9 GB: 3-of-4   1.2 GB: 4-of-4
Supported Languageszh en
Model ArchitectureLlamaForCausalLM
Licensellama3
Context Length8192
Model Max Length8192
Transformers Version4.40.2
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|end_of_text|>
Vocabulary Size128258
Torch Data Typebfloat16

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...a 3 70B Instruct Gradient 524K512K / 141.9 GB1023
...a 3 70B Instruct Gradient 262K256K / 141.9 GB2256
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...ama 3 70B Arimas Story RP V1.6256K / 141.2 GB130
...ama 3 70B Arimas Story RP V1.5256K / 141.2 GB73
Llama 3.1 70B Instruct128K / 141.9 GB1051044902
Note: green Score (e.g. "73.2") means that the model is better than yentinglin/Llama-3-Taiwan-8B-Instruct.

Rank the Llama 3 Taiwan 8B Instruct 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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