---
library_name: transformers
tags:
  - translation
  - english-to-italian
  - nlp
  - MarianMT
---

# Model Card for lucio94c/ita_to_eng

This model is a fine-tuned neural machine translation (NMT) model for translating text from **Italian to English** using the Hugging Face 🤗 `transformers` library.

## Model Details

### Model Description

This model is based on the pre-trained [Helsinki-NLP/opus-mt-it-en](https://huggingface.co/Helsinki-NLP/opus-mt-it-en) MarianMT architecture and has been fine-tuned on additional parallel Italian–English data for improved translation quality on general and informal texts.

- **Developed by:** [Lucio Ciracì](https://huggingface.co/lucio94c)
- **Model type:** Sequence-to-sequence neural translation (MarianMT)
- **Language(s) (NLP):** Italian → English
- **License:** MIT (or match the original model’s license if not MIT)
- **Finetuned from model:** Helsinki-NLP/opus-mt-it-en

### Model Sources

- **Repository:** [https://huggingface.co/lucio94c/ita_to_eng](https://huggingface.co/lucio94c/ita_to_eng)
- **Paper [optional]:** [MarianMT: Fast Neural Machine Translation in C++](https://arxiv.org/abs/2006.06687)

## Uses

### Direct Use

- Translate Italian text into English for documents, emails, or general understanding.
- Useful for language learners, travelers, or anyone needing fast Italian-to-English translation.

### Downstream Use

- Can be fine-tuned further for specific domains (e.g., legal, medical, technical).

### Out-of-Scope Use

- Not suitable for translating highly domain-specific or sensitive content without further fine-tuning.
- Not designed for translating code or non-natural language text.

## Bias, Risks, and Limitations

- The model may reflect biases present in the training data.
- Quality may decrease on slang, dialects, or specialized terminology.
- Automatic translations can contain errors; always review important text.

### Recommendations

- Review translations, especially for professional or sensitive contexts.
- Do not use for critical translations (medical, legal, etc.) without human verification.

## How to Get Started with the Model

```python
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer

model = AutoModelForSeq2SeqLM.from_pretrained("lucio94c/ita_to_eng")
tokenizer = AutoTokenizer.from_pretrained("lucio94c/ita_to_eng")

text = "Ciao, come stai?"
inputs = tokenizer(text, return_tensors="pt")
output = model.generate(**inputs)
print(tokenizer.decode(output[0], skip_special_tokens=True))