metadata

widget:
  - text: አዲስ አበባ
    example_title: Example 1
  - text: በኢንግሊዝ ፕሪምየር ሊግ
    example_title: Example 2
  - text: ዶናልድ ትራምፕ
    example_title: Example 3
language:
  - am
metrics:
  - perplexity
library_name: transformers
pipeline_tag: text-generation
base_model:
  - meta-llama/Llama-3.2-1B-Instruct

Llama-3.2-Amharic-1B

This model is a version of Meta's Llama-3.2-1B decoder transformer model that was continuously pretrained on an Amharic text corpus.

16k new amharic tokens were added to the Llama 3.2 tokenizer and the embdedding layer of the model was resized accordingly.
The model was then trained on 300 million tokens of Amharic text.
This is a base model. The Amharic instruction following version is Llama-3.2-1B-Amharic-Instruct

How to use

First, you need to install the latest version of transformers

pip install -Uq transformers

You can use this model directly with a pipeline for text generation:

from transformers import pipeline

llama_am = pipeline(
    "text-generation",
    model="rasyosef/Llama-3.2-1B-Amharic",
    device_map="auto"
  )

prompt = "በኢንግሊዝ ፕሪምየር ሊግ"
llama_am(
    prompt,
    max_new_tokens=128,
    temperature=0.3,
    do_sample=True,
    top_k=8,
    top_p=0.8,
    repetition_penalty=1.05
  )

Output:

[{'generated_text': 'በኢንግሊዝ ፕሪምየር ሊግ የ2017/18 የውድድር ዘመን ላይ ተሳታፊ የሆነው ሊቨርፑል ትናንት ምሽት 3 :45 ላይ ከዌስትሀም ዩናይትድ ጋር ባደረገው ጨዋታ በ2 ለ 1 ውጤት ተሸንፏል ።'}]