Create README.md

README.md

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+# NLLB-600M Finetuned for Robustness
+We finetuned NLLB-200-distilled-600M using adapters for robustness to ASR and synthetic non-native speakers noise.
+
+## How to use
+
+Start by installing transformers with NLLB-200 model with added adapters
+```bash
+git clone https://gitlab.com/horizon-europe-voxreality/multilingual-translation/speech-translation-demo.git
+cd speech-translation-demo
+# You might need to switch to dev branch
+pip install -e transformers
+```
+And now we can use the model:
+```python
+
+model_name = 'voxreality/nllb-asr-synthetic-robust'
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = M2M100ForConditionalGenerationWithAdapters.from_pretrained(model_name)
+
+src_lang = 'eng_Latn'
+tgt_lang = 'deu_Latn'
+
+input_text = "This is a good day"
+
+tokenizer.src_lang = src_lang
+inputs = tokenizer(input_text, return_tensors='pt').to(model.device)
+model_output = model.generate(**inputs,
+                              forced_bos_token_id=tokenizer.lang_code_to_id[tgt_lang])
+output_text = tokenizer.batch_decode(model_output, skip_special_tokens=True)[0]
+
+print(output_text)
+
+```