File size: 2,127 Bytes
5ab419d 5dfb023 4a5e650 5ab419d 5dfb023 8efcba2 5dfb023 302a420 5dfb023 302a420 5dfb023 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 |
---
license: apache-2.0
datasets:
- opus_books
- iwslt2017
language:
- en
- nl
metrics:
- sacrebleu
pipeline_tag: text2text-generation
tags:
- translation
widget:
- text: ">>en<< Was het leuk?"
---
**NOTE:** This is a work-in-progress model that is **not** considered finished. Keep this in mind when using this model, or continue training this model.
# Model Card for mt5-small nl-en translation
The mt5-small nl-en translation model is a finetuned version of [google/mt5-small](https://huggingface.co./google/mt5-small).
It was finetuned on 237k rows of the [iwslt2017](https://huggingface.co./datasets/iwslt2017/viewer/iwslt2017-en-nl) dataset and roughly 38k rows of the [opus_books](https://huggingface.co./datasets/opus_books/viewer/en-nl) dataset. The model was trained in multiple phases with different epochs & batch sizes.
## How to use
**Install dependencies**
```bash
pip install transformers, sentencepiece, protobuf
```
You can use the following code for model inference. This model was finetuned to work with an identifier when prompted that needs to be present for the best results.
```Python
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer, GenerationConfig
tokenizer = AutoTokenizer.from_pretrained("Michielo/mt5-small_nl-en_translation")
model = AutoModelForSeq2SeqLM.from_pretrained("Michielo/mt5-small_nl-en_translation")
translation_generation_config = GenerationConfig(
num_beams=4,
early_stopping=True,
decoder_start_token_id=0,
eos_token_id=model.config.eos_token_id,
pad_token=model.config.pad_token_id,
)
translation_generation_config.save_pretrained("/tmp", "translation_generation_config.json")
generation_config = GenerationConfig.from_pretrained("/tmp", "translation_generation_config.json")
inputs = tokenizer(">>en<< Your dutch text here", return_tensors="pt")
outputs = model.generate(**inputs, generation_config=generation_config)
print(tokenizer.batch_decode(outputs, skip_special_tokens=True))
```
## License
This project is licensed under the Apache License 2.0 - see the [LICENSE](https://www.apache.org/licenses/LICENSE-2.0) file for details. |