What are the hardware requirements for Llama3 8B Cpt Sea Lionv2 Base?

Llama3 8B Cpt Sea Lionv2 Base requires approximately 16.1 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama3 8B Cpt Sea Lionv2 Base and how large is it?

Llama3 8B Cpt Sea Lionv2 Base is developed by aisingapore, a model with 8b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Llama3 8B Cpt Sea Lionv2 Base?

Llama3 8B Cpt Sea Lionv2 Base is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama3 8B Cpt Sea Lionv2 Base by aisingapore — VRAM 16.1GB, 8K context

Name: Llama3 8B Cpt Sea Lionv2 Base
Author: aisingapore

Llama3 8B Cpt Sea Lionv2 Base is an open-source language model by aisingapore. Features: 8b LLM, VRAM: 16.1GB, Context: 8K, License: llama3, Instruction-Based, LLM Explorer Score: 0.14.

Arxiv:2101.09635 Arxiv:2309.06085 Autotrain compatible Base model:finetune:meta-llama... Base model:meta-llama/meta-lla... En Endpoints compatible Id Instruct Llama Region:us Safetensors Sharded Ta Tensorflow Th Vi

Model Card on HF 🤗: https://huggingface.co/aisingapore/llama3-8b-cpt-sea-lionv2-base

Llama3 8B Cpt Sea Lionv2 Base Parameters and Internals

Model Type

Decoder

Additional Notes

The model has not been aligned for safety. Developers and users should perform their own safety fine-tuning and related security measures.

Supported Languages

en (English), id (Indonesian), th (Thai), vi (Vietnamese), ta (Tamil)

Training Details

Data Sources:

Dolma RefinedWeb - English, Dolma C4 - English, Dolma Reddit - English, Dolma Semantic Scholar, Dolma arXiv, Dolma StarCoder, SEA-LION Pile - Indonesian, Wiki* - Indonesian, SEA-LION Pile - Tamil, Wiki* + News - Tamil, SEA-LION Pile - Thai, WangChanBERTa - Thai, Wiki* - Thai, SEA-LION Pile - Vietnamese, Wiki* - Vietnamese

Data Volume:

48 billion tokens

Methodology:

Continued pre-training from Meta-Llama-3-8B-Instruct

Training Time:

2 days

Hardware Used:

AWS EC2 p5d.24xlarge instances - 8, Nvidia H100 80GB GPU - 64

LLM Name	Llama3 8B Cpt Sea Lionv2 Base
Repository 🤗	https://huggingface.co/aisingapore/llama3-8b-cpt-sea-lionv2-base
Base Model(s)	Meta Llama 3 8B Instruct meta-llama/Meta-Llama-3-8B-Instruct
Model Size	8b
Required VRAM	16.1 GB
Updated	2025-04-13
Maintainer	aisingapore
Model Type	llama
Instruction-Based	Yes
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 Languages	en id ta th vi
Model Architecture	LlamaForCausalLM
License	llama3
Context Length	8192
Model Max Length	8192
Transformers Version	4.42.3
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	128256
Torch Data Type	bfloat16

Rank the Llama3 8B Cpt Sea Lionv2 Base capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

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

Best Alternatives to Llama3 8B Cpt Sea Lionv2 Base

Best Alternatives	Context / RAM	Downloads	Likes
...otron 8B UltraLong 4M Instruct	4192K / 32.1 GB	1135	125
UltraLong Thinking	4192K / 16.1 GB	2	3
...a 3.1 8B UltraLong 4M Instruct	4192K / 32.1 GB	176	24
...a 3.1 8B UltraLong 2M Instruct	2096K / 32.1 GB	875	9
...otron 8B UltraLong 2M Instruct	2096K / 32.1 GB	124	18
Cthulhu 8B V1.4	1048K / 16.1 GB	10	10
...raLong 1M Instruct Abliterated	1048K / 32.1 GB	4	9
...a 3.1 8B UltraLong 1M Instruct	1048K / 32.1 GB	1387	29
...otron 8B UltraLong 1M Instruct	1048K / 32.1 GB	702	59
Zero Llama 3.1 8B Beta6	1048K / 16.1 GB	7	1

Note: green Score (e.g. "73.2") means that the model is better than aisingapore/llama3-8b-cpt-sea-lionv2-base.