# Low-resource translation

An English-Zamboanga Chavacano translation model fine-tuned based on mbart-large-50-many-to-many-mmt, achieving a BLEU score of 37.74

This model is a quantized version converted from google-t5/t5-small to GGUF format using llama.cpp via ggml.ai's GGUF-my-repo space.

T5-small fine-tuned English-Nepali neural machine translation model with a BLEU score of 13.86

This is a translation model trained via AutoTrain, supporting translation tasks between unknown languages.

This model is a fine-tuned Arabic (Dz) to English translation model based on the distilled version of NLLB-200

A Hindi to English translation model fine-tuned based on the google/mt5-small pre-trained model

ONNX export version of T5-small model, supporting multilingual text generation and translation tasks.

Pre-trained T5 small standard Malay language model supporting multiple natural language processing tasks.

This is a Bengali-to-English machine translation model based on the Transformer architecture, developed by the Helsinki-NLP team.

This is a Vietnamese-to-Spanish machine translation model based on the transformer-align architecture, developed by the Helsinki-NLP team and released under the Tatoeba-Challenge project.

This is a Hindi-to-Urdu machine translation model based on the transformer-align architecture, released by the Tatoeba-Challenge project.

A Transformer-based machine translation model from Polish to Norwegian, supporting translation tasks for both Bokmål (nob) and Nynorsk (nno).

This is an English to Urdu machine translation model based on the transformer-align architecture, developed by the Helsinki-NLP team.

This is a machine translation model from Catalan to Ukrainian based on the transformer-align architecture, released by the Tatoeba-Challenge project.