Gemma2-2B-Swahili-Preview is a Swahili variation of the base language model Gemma2 2B fine-tuned on the Inkuba-Mono Swahili dataset, designed to enhance Swahili language understanding through monolingual training.

Model Details

Developer: Alfaxad Eyembe
Base Model: google/gemma-2-2b
Model Type: Decoder-only transformer
Language: Swahili
License: Apache 2.0
Fine-tuning Approach: Low-Rank Adaptation (LoRA)

Training Data

The model was fine-tuned on a focused subset of the Inkuba-Mono dataset:

1,000,000 randomly selected examples
Total tokens: 60,831,073
Average text length: 101.33 characters
Diverse Swahili text sources including news, social media, and various domains

Training Details

Fine-tuning Method: LoRA
Training Steps: 2,500
Batch Size: 2
Gradient Accumulation Steps: 32
Learning Rate: 2e-4
Training Time: ~7.5 hours

Model Capabilities

This model is designed for:

Swahili text continuation
Natural language understanding
Contextual text generation
Base language modeling for Swahili

Usage

python

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

tokenizer = AutoTokenizer.from_pretrained("alfaxadeyembe/gemma2-2b-swahili-preview")
model = AutoModelForCausalLM.from_pretrained(
    "alfaxadeyembe/gemma2-2b-swahili-preview",
    device_map="auto",
    torch_dtype=torch.bfloat16
)

# Set to evaluation mode
model.eval()

# Example usage
prompt = "Katika soko la Kariakoo, teknolojia mpya imewezesha"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(
    **inputs,
    max_new_tokens=500,
    do_sample=True,
    temperature=0.7,
    top_p=0.95
)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response)

Key Features

Natural Swahili text continuation
Strong cultural context understanding
Efficient parameter updates through LoRA
Diverse domain knowledge integration

Limitations

Not instruction-tuned
Base language modeling capabilities
Performance varies across different text domains

Citation

bibtex

@misc{gemma2-2b-swahili-preview,
  author = {Alfaxad Eyembe},
  title = {Gemma2-2B-Swahili-Preview: Swahili Variation of Gemma2 2B},
  year = {2025},
  publisher = {Hugging Face},
  journal = {Hugging Face Model Hub},
}

Contact

For questions or feedback, please reach out through:

HuggingFace: @alfaxadeyembe
X : @alfxad

Alfaxad/gemma2-2b-swahili-preview

Gemma2-2B-Swahili-Preview