
## MuRIL - Unofficial

Multilingual Representations for Indian Languages : Google open sourced
this BERT model pre-trained on 17 Indian languages, and their transliterated
counterparts.

The model was trained using a self-supervised masked language modeling task. We do whole word masking with a maximum of 80 predictions. The model was trained for 1000K steps, with a batch size of 4096, and a max sequence length of 512.

Original model on TFHub: https://tfhub.dev/google/MuRIL/1

*Official release now on HuggingFace (March 2021)* https://huggingface.co/google/muril-base-cased

License: Apache 2.0

### About this upload

I ported the TFHub .pb model to .h5 and then pytorch_model.bin for
compatibility with Transformers.

{"language": ["en", "hi", "bn", "ta", "as", "gu", "kn", "ks", "ml", "mr", "ne", "or", "pa", "sa", "sd", "te", "ur", "multilingual"], "license": "apache-2.0"}
transformers pytorch tf jax safetensors bert fill-mask en hi bn ta as gu kn ks ml mr ne or pa sa sd te ur multilingual license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #en #hi #bn #ta #as #gu #kn #ks #ml #mr #ne #or #pa #sa #sd #te #ur #multilingual #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 


## MuRIL - Unofficial

Multilingual Representations for Indian Languages : Google open sourced
this BERT model pre-trained on 17 Indian languages, and their transliterated
counterparts.

The model was trained using a self-supervised masked language modeling task. We do whole word masking with a maximum of 80 predictions. The model was trained for 1000K steps, with a batch size of 4096, and a max sequence length of 512.

Original model on TFHub: URL

*Official release now on HuggingFace (March 2021)* URL

License: Apache 2.0

### About this upload

I ported the TFHub .pb model to .h5 and then pytorch_model.bin for
compatibility with Transformers.

## MuRIL - Unofficial

Multilingual Representations for Indian Languages : Google open sourced
this BERT model pre-trained on 17 Indian languages, and their transliterated
counterparts.

The model was trained using a self-supervised masked language modeling task. We do whole word masking with a maximum of 80 predictions. The model was trained for 1000K steps, with a batch size of 4096, and a max sequence length of 512.

Original model on TFHub: URL

*Official release now on HuggingFace (March 2021)* URL

License: Apache 2.0 ### About this upload

I ported the TFHub .pb model to .h5 and then pytorch_model.bin for
compatibility with Transformers.
TAGS
#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #en #hi #bn #ta #as #gu #kn #ks #ml #mr #ne #or #pa #sa #sd #te #ur #multilingual #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ## MuRIL - Unofficial

Multilingual Representations for Indian Languages : Google open sourced
this BERT model pre-trained on 17 Indian languages, and their transliterated
counterparts.

The model was trained using a self-supervised masked language modeling task. We do whole word masking with a maximum of 80 predictions. The model was trained for 1000K steps, with a batch size of 4096, and a max sequence length of 512.

Original model on TFHub: URL

*Official release now on HuggingFace (March 2021)* URL

License: Apache 2.0 ### About this upload

I ported the TFHub .pb model to .h5 and then pytorch_model.bin for
compatibility with Transformers.
passage: TAGS
#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #en #hi #bn #ta #as #gu #kn #ks #ml #mr #ne #or #pa #sa #sd #te #ur #multilingual #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
## MuRIL - Unofficial

Multilingual Representations for Indian Languages : Google open sourced
this BERT model pre-trained on 17 Indian languages, and their transliterated
counterparts.

The model was trained using a self-supervised masked language modeling task. We do whole word masking with a maximum of 80 predictions. The model was trained for 1000K steps, with a batch size of 4096, and a max sequence length of 512.

Original model on TFHub: URL

*Official release now on HuggingFace (March 2021)* URL

License: Apache 2.0### About this upload

I ported the TFHub .pb model to .h5 and then pytorch_model.bin for
compatibility with Transformers.