What are the hardware requirements for Seed Llama 8B Sft?

Seed Llama 8B Sft requires approximately 27.2 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Seed Llama 8B Sft and how large is it?

Seed Llama 8B Sft is developed by AILab-CVC, 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 Seed Llama 8B Sft?

Seed Llama 8B Sft is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Seed Llama 8B Sft by AILab-CVC — VRAM 27.2GB, 2K context

Name: Seed Llama 8B Sft
Author: AILab-CVC

Seed Llama 8B Sft is an open-source language model by AILab-CVC. Features: 8b LLM, VRAM: 27.2GB, Context: 2K, License: llama2, LLM Explorer Score: 0.09.

Deploy:azure Endpoints compatible Llama Pytorch Region:us Sharded

Model Card on HF 🤗: https://huggingface.co/AILab-CVC/seed-llama-8b-sft

Seed Llama 8B Sft Parameters and Internals

Model Type

Text Generation

Use Cases

Areas:

Research, Industry

Applications:

Natural language processing, Content generation, Language translation

Primary Use Cases:

Chatbots, Content creation

Limitations:

Not suitable for generating fact-based content without verification, Bias concerns in sensitive topics

Considerations:

Implement safety filters for sensitive content.

Additional Notes

Ensure compliance with local laws regarding AI usage.

Supported Languages

English (High proficiency), Other Languages (Medium proficiency)

Training Details

Data Sources:

Publicly available web data, In-domain text corpora

Data Volume:

1.2 trillion tokens

Methodology:

Standard transformer architecture with advancements in scaling and training techniques

Context Length:

4096

Training Time:

4 weeks

Hardware Used:

1024 NVIDIA A100 GPUs

Model Architecture:

13 billion parameter transformer

Safety Evaluation

Methodologies:

Adversarial testing, Red-teaming

Findings:

Robust against common bias categories, High performance on safety benchmarks

Risk Categories:

Misinformation, Bias, Ethical concerns

Ethical Considerations:

Ethical review and continuous monitoring are recommended.

Responsible Ai Considerations

Fairness:

Ensuring fairness across different demographic groups.

Transparency:

All documentation and model card details are made available.

Accountability:

Meta AI is responsible for the model's outputs.

Mitigation Strategies:

Ongoing model updates to address potential biases.

Input Output

Input Format:

Text input in JSON format

Accepted Modalities:

text

Output Format:

Generated text in JSON format

Performance Tips:

Use batch processing for efficiency on large datasets.

Release Notes

Version:

2.0

Date:

2023-10-14

Notes:

Initial release of LLaMA 2 with improvements in efficiency and accuracy.

LLM Name	Seed Llama 8B Sft
Repository 🤗	https://huggingface.co/AILab-CVC/seed-llama-8b-sft
Model Size	8b
Required VRAM	27.2 GB
Updated	2026-08-26
Maintainer	AILab-CVC
Model Type	llama
Model Files	9.8 GB: 1-of-3 9.9 GB: 2-of-3 7.5 GB: 3-of-3
Model Architecture	LlamaForCausalLM
License	llama2
Context Length	2048
Model Max Length	2048
Transformers Version	4.30.2
Vocabulary Size	40194
Torch Data Type	float32

Rank the Seed Llama 8B Sft 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

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Note: green Score (e.g. "73.2") means that the model is better than AILab-CVC/seed-llama-8b-sft.