| --- |
| license: apache-2.0 |
| language: |
| - en |
| - eu |
| metrics: |
| - BLEU |
| - TER |
| --- |
| ## Medical English-Basque machine translation model |
|
|
| ## Model description |
|
|
| - **Model type:** translation |
| - **Source Language:** English |
| - **Target Language:** Basque |
| - **License:** apache-2.0 |
|
|
| ## How to Get Started with the Model |
|
|
| Use the code below to get started with the model. |
|
|
| ``` |
| from transformers import MarianMTModel, MarianTokenizer |
| from transformers import AutoTokenizer |
| from transformers import AutoModelForSeq2SeqLM |
| |
| src_text = ["The patient had brain damage"] |
| |
| model_name = "anegda/medical_en-eu" |
| tokenizer = MarianTokenizer.from_pretrained(model_name) |
| |
| model = AutoModelForSeq2SeqLM.from_pretrained(model_name) |
| translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True)) |
| print([tokenizer.decode(t, skip_special_tokens=True) for t in translated])` |
| ``` |
|
|
| The recommended environments include the following transfomer versions: 4.12.3 , 4.15.0 , 4.26.1 |
|
|
| ### Contact information |
| For further information, send an email to <ane.garciad@ehu.eus> |
|
|
