widget, language, metrics, library_name, pipeline_tag, base_model

widget	language	metrics	library_name	pipeline_tag	base_model
text example_title አዲስ አበባ Example 1 text example_title በኢንግሊዝ ፕሪምየር ሊግ Example 2 text example_title ዶናልድ ትራምፕ Example 3	am	perplexity	transformers	text-generation	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 ።'}]