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pmmlv2-fine-tuned-igbo

Sentence Similarity
sentence-transformers
Safetensors
Transformers
bert
feature-extraction
text-embeddings-inference
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pmmlv2-fine-tuned-igbo
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---
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
- ig
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-igbo

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

[Igbo](https://en.wikipedia.org/wiki/Igbo_language) words, like those in [Yoruba](https://en.wikipedia.org/wiki/Yoruba_language), are composed of different combinations of vowels and consonants. The Igbo language has a complex phonetic system featuring twenty-eight consonant sounds and eight vowels. Igbo words can range from simple to intricate in their structure, but they adhere to specific patterns of syllable formation and pronunciation. Igbo employs three distinct tones to distinguish meaning: high, low, and downstep. These tones are indicated by diacritical marks, such as acute accents (´), grave accents (`), and macrons (¯), required for accurate pronunciation and comprehension. Furthermore, Igbo words may include digraphs (two-letter combinations representing a single sound) and diphthongs (gliding vowel sounds), adding to the language's phonological richness.

### 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 = ["Unu bụcha ezigbo mmadụ", "Anyị bụcha ezigbo mmadụ"]

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

### License

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

### Copyright

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