README.md

---
library_name: transformers
license: apache-2.0
datasets:
- billingsmoore/tibetan-to-english-translation-dataset
language:
- bo
- en
metrics:
- bleu
base_model:
- billingsmoore/tibetan-to-english-translation
---

# Model Card for tibetan-to-english-translation-4bit

## Model Details

This model is a quantized version of [**billingsmoore/tibetan-to-english-translation**](https://huggingface.co/billingsmoore/tibetan-to-english-translation). The model is double quanitized to 4bits. The process was performed (and can be replicated) with the following code:

```python
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, BitsAndBytesConfig
import torch

model_id = "billingsmoore/tibetan-to-english-translation"

tokenizer = AutoTokenizer.from_pretrained(model_id)

quantization_config =  BitsAndBytesConfig(
   load_in_4bit=True,
   bnb_4bit_quant_type="nf4",
   bnb_4bit_use_double_quant=True,
   bnb_4bit_compute_dtype=torch.bfloat16
)

model = AutoModelForSeq2SeqLM.from_pretrained(model_id, device_map="auto", quantization_config=quantization_config)
```

- **Developed by:** billingsmoore
- **Model type:** Seq2Seq
- **Language(s) (NLP):** Tibetan, English
- **License:** Apache license 2.0

### Model Sources 

- **Repository:** [GitHub](https://github.com/billingsmoore/MLotsawa)

## Uses

The intended usage of this quantized model is for in-browser usage on edge devices.

### Direct Use

This model can be used as part of a web app using Transformers.js as below.

```js
import { pipeline } from '@huggingface/transformers';

// Allocate a pipeline for sentiment-analysis
const pipe = await pipeline('translation', 'billingsmoore/tibetan-to-english-translation-4bit');

const out = await pipe('ན་མོ་མཉྫ་ཤཱི་ཡེ།');
```

### Out-of-Scope Use

This model can also be used in the usual way using the Python transformers library as below.

```python
from transformers import pipeline

# Allocate a pipeline for sentiment-analysis
pipe = pipeline('translation', 'billingsmoore/tibetan-to-english-translation-4bit')

out = pipe('ན་མོ་མཉྫ་ཤཱི་ཡེ།')
```

## More Information

For additional information on training, data, etc. please see the model card for [**billingsmoore/tibetan-to-english-translation**](https://huggingface.co/billingsmoore/tibetan-to-english-translation).

## Model Card Author

billingsmoore

## Model Card Contact

billingsmoore [at] gmail [dot] com