Update README.md

README.md

@@ -14,7 +14,7 @@ metrics:
 pipeline_tag: translation
 ---
 
-# OPUS-MT-tiny-fra-eng
+# OPUS-MT-tiny-eng-deu
 
 Distilled model from a Tatoeba-MT Teacher: [OPUS-MT-models/en-de/opus-2020-02-26](https://object.pouta.csc.fi/OPUS-MT-models/en-de/opus-2020-02-26.zip), which has been trained on the [Tatoeba](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/data) dataset.
 
@@ -25,7 +25,7 @@ The configuration file fed into OpusDistillery can be found [here](https://githu
 ## How to run
 ```python
 from transformers import MarianMTModel, MarianTokenizer
-model_name = "Helsinki-NLP/opus-mt_tiny_fra-eng"
+model_name = "Helsinki-NLP/opus-mt_tiny_eng-deu"
 tokenizer = MarianTokenizer.from_pretrained(model_name)
 model = MarianMTModel.from_pretrained(model_name)
 tok = tokenizer("Hello, how are you?", return_tensors="pt").input_ids
@@ -48,3 +48,13 @@ tokenizer.decode(output, skip_special_tokens=True)
 | Bouquet 	|  31.8 |  58.2 | 0.8260 |
 
 
+## Marian models
+
+We also provide Marian-compatible versions of this model. To use them, compile [Marian](https://marian-nmt.github.io/quickstart/) and run decoding with `marian-decoder`, for example:
+
+```bash
+marian-decoder \
+  -i input.txt \
+  -c final.model.npz.best-perplexity.npz.decoder.yml \
+  -m final.model.npz.best-perplexity.npz \
+  -v vocab.spm vocab.spm