
mBART (a pre-trained model by Facebook) is pre-trained to de-noise multiple languages simultaneously with BART objective.

Checkpoint available in this repository is obtained after fine-tuning `facebook/mbart-large-cc25` on all samples (~260K) from Bhasha (pib_v1.3) Hindi-English parallel corpus. This checkpoint gives decent results for Hindi-english translation.
{"datasets": "pib", "widget": [{"text": "\u0928\u092e\u0938\u094d\u0924\u0947! \u092e\u0948\u0902 \u0935\u093e\u0938\u0941\u0926\u0947\u0935 \u0917\u0941\u092a\u094d\u0924\u093e \u0939\u0942\u0902"}]}
transformers pytorch mbart text2text-generation dataset:pib autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #mbart #text2text-generation #dataset-pib #autotrain_compatible #endpoints_compatible #has_space #region-us 


mBART (a pre-trained model by Facebook) is pre-trained to de-noise multiple languages simultaneously with BART objective.

Checkpoint available in this repository is obtained after fine-tuning 'facebook/mbart-large-cc25' on all samples (~260K) from Bhasha (pib_v1.3) Hindi-English parallel corpus. This checkpoint gives decent results for Hindi-english translation.
TAGS
#transformers #pytorch #mbart #text2text-generation #dataset-pib #autotrain_compatible #endpoints_compatible #has_space #region-us 

passage: TAGS
#transformers #pytorch #mbart #text2text-generation #dataset-pib #autotrain_compatible #endpoints_compatible #has_space #region-us 
