---
language:
- ne
- en
tags:
- translation
- fairseq
- fsmt
license: apache-2.0
---

# Nepali-Tamang-English Machine Translation Model

This model was converted from a Fairseq checkpoint to Hugging Face Transformers format. It performs machine translation between Nepali, Tamang, and English.

## Model Details
- **Architecture:** FSMT (Fairseq Machine Translation)
- **Original Framework:** Fairseq
- **Languages:** Nepali (ne), Tamang, English (en)

## Usage

You can use this model directly with the Hugging Face `transformers` library.

### Installation
```bash
pip install transformers
```

### Python Example
```python
from transformers import FSMTForConditionalGeneration, FSMTTokenizer

mname = "rishi70612/nepali-tamang-english-mt"
tokenizer = FSMTTokenizer.from_pretrained(mname)
model = FSMTForConditionalGeneration.from_pretrained(mname)

input_text = "Hugging Face is a technology company based in New York and Paris." # Replace with your source text
input_ids = tokenizer.encode(input_text, return_tensors="pt")
outputs = model.generate(input_ids)
decoded = tokenizer.decode(outputs[0], skip_special_tokens=True)

print(decoded)
```

## Note on Languages
Since this is a custom model, ensure you handle input text preprocessing (like language tags) if required by your specific training setup. The tokenizer is configured with BPE.