What are the hardware requirements for Llama3 8B Cpt Sea Lionv2.1 Instruct?

Llama3 8B Cpt Sea Lionv2.1 Instruct 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 Lionv2.1 Instruct and how large is it?

Llama3 8B Cpt Sea Lionv2.1 Instruct 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 Lionv2.1 Instruct?

Llama3 8B Cpt Sea Lionv2.1 Instruct 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 Lionv2.1 Instruct by aisingapore — VRAM 16.1GB, 8K context

Name: Llama3 8B Cpt Sea Lionv2.1 Instruct
Author: aisingapore

Llama3 8B Cpt Sea Lionv2.1 Instruct is an open-source language model by aisingapore. Features: 8b LLM, VRAM: 16.1GB, Context: 8K, License: llama3, Instruction-Based, LLM Explorer Score: 0.16.

Arxiv:2306.05685 Arxiv:2309.06085 Arxiv:2311.07911 Autotrain compatible Base model:aisingapore/llama3-... Base model:finetune:aisingapor... Conversational 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-lionv2.1-instruct

Llama3 8B Cpt Sea Lionv2.1 Instruct Parameters and Internals

Model Type

Decoder

Use Cases

Areas:

research, commercial applications

Limitations:

can hallucinate, occasionally generates irrelevant content, potential inconsistencies in reasoning

Considerations:

Users should validate model responses for accuracy and relevance.

Supported Languages

en (fluent), id (fluent), ta (fluent), th (fluent), vi (fluent)

Training Details

Data Volume:

100,000 English instruction-completion pairs, 50,000 other ASEAN languages

Methodology:

Fine-tuned with additional supervised alignment using LoRA

Context Length:

8192

Hardware Used:

8x A100-40GB

Model Architecture:

Llama3 architecture

Input Output

Input Format:

JSON structured prompt message format

Accepted Modalities:

text

Output Format:

Textual response

LLM Name	Llama3 8B Cpt Sea Lionv2.1 Instruct
Repository 🤗	https://huggingface.co/aisingapore/llama3-8b-cpt-sea-lionv2.1-instruct
Base Model(s)	Llama3 8B Cpt Sea Lionv2 Base aisingapore/llama3-8b-cpt-sea-lionv2-base
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	4.44.0
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|eot_id\|>
Vocabulary Size	128256
Torch Data Type	bfloat16

Rank the Llama3 8B Cpt Sea Lionv2.1 Instruct 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 Lionv2.1 Instruct

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-lionv2.1-instruct.