tacab/somali-agriculture

Somali Agriculture GPT-2 Model

This is a GPT-2 language model trained on ~10,000 Somali prompt-response pairs related to agriculture. The goal is to help generate Somali text for agricultural questions and educational content.

Model Details

• Architecture: GPT-2 (4 layers, 4 attention heads)
• Vocabulary: Custom trained Byte-Pair Encoding tokenizer
• Training Data: 10,000 prompt-response pairs in Somali language
• Epochs: 5
• Embedding Size: 256
• Context Length: 512 tokens

Intended Use

This model can be used to:

• Generate Somali answers to agricultural questions
• Create educational materials for Somali farmers
• Build Somali chatbots focused on agriculture

Example Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("tacab/somali-agriculture")
tokenizer = AutoTokenizer.from_pretrained("tacab/somali-agriculture")

prompt = "Maxay tahay faa'iidada bacriminta?"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_length=100)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))