
# DistilBERT base multilingual model Spanish subset (cased)

This model is the Spanish extract of `distilbert-base-multilingual-cased` (https://huggingface.co/distilbert-base-multilingual-cased), a distilled version of the [BERT base multilingual model](bert-base-multilingual-cased). This model is cased: it does make a difference between english and English.

It uses the extraction method proposed by Geotrend described in https://github.com/Geotrend-research/smaller-transformers. 

The resulting model has the same architecture as DistilmBERT: 6 layers, 768 dimension and 12 heads, with a total of **63M parameters** (compared to 134M parameters for DistilmBERT).

The goal of this model is to reduce even further the size of the `distilbert-base-multilingual` multilingual model by selecting only most frequent tokens for Spanish, reducing the size of the embedding layer. For more details visit the paper from the Geotrend team: Load What You Need: Smaller Versions of Multilingual BERT.
{"language": "es", "license": "apache-2.0", "datasets": ["wikipedia"], "widget": [{"text": "Mi nombre es Juan y vivo en [MASK]."}]}
transformers pytorch safetensors distilbert fill-mask es dataset:wikipedia license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #distilbert #fill-mask #es #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 


# DistilBERT base multilingual model Spanish subset (cased)

This model is the Spanish extract of 'distilbert-base-multilingual-cased' (URL a distilled version of the BERT base multilingual model. This model is cased: it does make a difference between english and English.

It uses the extraction method proposed by Geotrend described in URL 

The resulting model has the same architecture as DistilmBERT: 6 layers, 768 dimension and 12 heads, with a total of 63M parameters (compared to 134M parameters for DistilmBERT).

The goal of this model is to reduce even further the size of the 'distilbert-base-multilingual' multilingual model by selecting only most frequent tokens for Spanish, reducing the size of the embedding layer. For more details visit the paper from the Geotrend team: Load What You Need: Smaller Versions of Multilingual BERT.
# DistilBERT base multilingual model Spanish subset (cased)

This model is the Spanish extract of 'distilbert-base-multilingual-cased' (URL a distilled version of the BERT base multilingual model. This model is cased: it does make a difference between english and English.

It uses the extraction method proposed by Geotrend described in URL 

The resulting model has the same architecture as DistilmBERT: 6 layers, 768 dimension and 12 heads, with a total of 63M parameters (compared to 134M parameters for DistilmBERT).

The goal of this model is to reduce even further the size of the 'distilbert-base-multilingual' multilingual model by selecting only most frequent tokens for Spanish, reducing the size of the embedding layer. For more details visit the paper from the Geotrend team: Load What You Need: Smaller Versions of Multilingual BERT.
TAGS
#transformers #pytorch #safetensors #distilbert #fill-mask #es #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 # DistilBERT base multilingual model Spanish subset (cased)

This model is the Spanish extract of 'distilbert-base-multilingual-cased' (URL a distilled version of the BERT base multilingual model. This model is cased: it does make a difference between english and English.

It uses the extraction method proposed by Geotrend described in URL 

The resulting model has the same architecture as DistilmBERT: 6 layers, 768 dimension and 12 heads, with a total of 63M parameters (compared to 134M parameters for DistilmBERT).

The goal of this model is to reduce even further the size of the 'distilbert-base-multilingual' multilingual model by selecting only most frequent tokens for Spanish, reducing the size of the embedding layer. For more details visit the paper from the Geotrend team: Load What You Need: Smaller Versions of Multilingual BERT.
passage: TAGS
#transformers #pytorch #safetensors #distilbert #fill-mask #es #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
# DistilBERT base multilingual model Spanish subset (cased)

This model is the Spanish extract of 'distilbert-base-multilingual-cased' (URL a distilled version of the BERT base multilingual model. This model is cased: it does make a difference between english and English.

It uses the extraction method proposed by Geotrend described in URL 

The resulting model has the same architecture as DistilmBERT: 6 layers, 768 dimension and 12 heads, with a total of 63M parameters (compared to 134M parameters for DistilmBERT).

The goal of this model is to reduce even further the size of the 'distilbert-base-multilingual' multilingual model by selecting only most frequent tokens for Spanish, reducing the size of the embedding layer. For more details visit the paper from the Geotrend team: Load What You Need: Smaller Versions of Multilingual BERT.