# BERT-Small-L-4_H-512_A-8
This is a port of the [BERT-Small model](https://github.com/google-research/bert) to Pytorch. It uses 4 layers, a hidden size of 512 and 8 attention heads. 
{}
transformers pytorch jax bert feature-extraction endpoints_compatible region:us
TAGS
#transformers #pytorch #jax #bert #feature-extraction #endpoints_compatible #region-us 

# BERT-Small-L-4_H-512_A-8
This is a port of the BERT-Small model to Pytorch. It uses 4 layers, a hidden size of 512 and 8 attention heads. 
# BERT-Small-L-4_H-512_A-8
This is a port of the BERT-Small model to Pytorch. It uses 4 layers, a hidden size of 512 and 8 attention heads.
TAGS
#transformers #pytorch #jax #bert #feature-extraction #endpoints_compatible #region-us 
 # BERT-Small-L-4_H-512_A-8
This is a port of the BERT-Small model to Pytorch. It uses 4 layers, a hidden size of 512 and 8 attention heads.
passage: TAGS
#transformers #pytorch #jax #bert #feature-extraction #endpoints_compatible #region-us 
# BERT-Small-L-4_H-512_A-8
This is a port of the BERT-Small model to Pytorch. It uses 4 layers, a hidden size of 512 and 8 attention heads.