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netFound-small
snlucsb/netFound-small
netFound-small is a machine learning model from snlucsb. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
netFound is a network traffic encoder model that uses transformer architecture and includes a pretraining phase on unlabeled data to achieve high results.
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At a glance
- License
- mit
- Model type
- netFound
- Access
- Public
- Created
- Mar 9, 2026
- Updated
- Mar 9, 2026
- SHA
- e27221df
Model card
From the Hugging Face model README
netFound-small
Description
netFound is a network traffic encoder model that uses transformer architecture and includes a pretraining phase on unlabeled data to achieve high results.
Key features:
- netFound takes raw PCAP data as input
- netFound can (and need) be pretrained on the unlabeled dataset
- netFound uses Hierarchical Transformer architecture to take into account packet burst and flow behavior
- netFound uses burst metadata (inter arrival time, number of bytes per burst, etc)
Details
- Model config: small (4 layers, 4 attention heads, 512 hidden size)
- Pretraining details: 128 GPUs, 45k steps, ~9bln tokens seen
Source code
- Type
- netFound
- License
- mit
- Created
- Mar 9, 2026
- Updated
- Mar 9, 2026