---
language:
- multilingual
- ar
- bg
- ca
- cs
- da
- de
- el
- en
- es
- et
- fa
- fi
- fr
- gl
- gu
- he
- hi
- hr
- hu
- hy
- id
- it
- ja
- ka
- ko
- ku
- lt
- lv
- mk
- mn
- mr
- ms
- my
- nb
- nl
- pl
- pt
- ro
- ru
- sk
- sl
- sq
- sr
- sv
- th
- tr
- uk
- ur
- vi
- yo
license: mit
library_name: sentence-transformers
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
language_bcp47:
- fr-ca
- pt-br
- zh-cn
- zh-tw
pipeline_tag: sentence-similarity
inference: false
---

## 0xnu/pmmlv2-fine-tuned-yoruba

Yoruba fine-tuned LLM using [sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2](https://huggingface.co/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2).

[Yoruba](https://en.wikipedia.org/wiki/Yoruba_language) words typically consist of various combinations of vowels and consonants. The Yoruba language has a rich phonetic structure, including eighteen consonants and seven vowels. Words in Yoruba can vary in length and complexity, but they generally follow consistent patterns of syllable structure and pronunciation. Additionally, Yoruba words may include diacritical marks such as accents and underdots to indicate tone and vowel length; they are essential to the language's phonology and meaning.

### Usage (Sentence-Transformers)

Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed:

```
pip install -U sentence-transformers
```

Then you can use the model like this:

```python
from sentence_transformers import SentenceTransformer
sentences = ["Kini olu ilu England", "Kini eranko ti o gbona julọ ni agbaye?"]

model = SentenceTransformer('0xnu/pmmlv2-fine-tuned-yoruba')
embeddings = model.encode(sentences)
print(embeddings)
```

### License

This project is licensed under the [MIT License](./LICENSE).

### Copyright

(c) 2024 [Finbarrs Oketunji](https://finbarrs.eu).