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README.md

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-license: mit
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+---
+license: mit
+---
+
+# 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
+
+https://github.com/SNL-UCSB/netFound