Downloads · 30 days
23
4% of all-time downloads
Nyehashai/Ntahokaja-0.31-Base
Ntahokaja-0.31-Base is a text generation model from Nyehashai. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
Ntahokaja 0.31 is the first sovereign Small Language Model (SLM) trained from scratch specifically for the Kirundi language. Developed by Nyehashi AI, it features a custom morphological tokenizer designed to respect B…
Downloads · 30 days
23
4% of all-time downloads
All-time downloads
518
Public
Parameters
91.2M
365 MB on disk
Likes
1
Public
Click a slice to open those files.
.safetensors365 MB · 100%
From the Hugging Face model README
Ntahokaja 0.31 is the first sovereign Small Language Model (SLM) trained from scratch specifically for the Kirundi language. Developed by Nyehashi AI, it features a custom morphological tokenizer designed to respect Bantu grammar and agglutinative logic.
This model requires custom tokenization logic. You must use trust_remote_code=True to load it correctly.
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "Nyehashai/Ntahokaja-0.31-Base"
tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id)
prompt = "Amategeko yu'Burundi avuga ko "
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_length=100, do_sample=True, temperature=0.7)
print(tokenizer.decode(outputs[0]))
Ntahokaja 0.31 is a 91,209,216-parameter Transformer-based language model. Unlike general models, it uses a Hybrid Morphological-BPE strategy. This version resolves the "word-boundary collapse" by using an explicit @@ sub-word joiner and ByteLevel space protection. Layers: 12 Attention Heads: 12 Context Window: 512 tokens Size: 347.9 MB (Safetensors)
Metric Value Validation Loss 3.24 (Optimal) Training Loss 1.26 Vocabulary Size 7,500 tokens Data Volume 18.1M tokens
The model demonstrates high-fidelity knowledge of Burundian geography (identifying provinces like Makamba, Kirundo, etc.) and political history. Notably, the model exhibits Implicit Moral Alignment, pivoting away from harmful or violent prompts toward themes of social respect and constitutional law.
This is a Foundational Base Model. It is designed for text continuation, linguistic research, and as a base for instruction fine-tuning. It is NOT a conversational assistant and has not been fine-tuned for QA yet.
If you use this model, please attribute the work to Nyehashi AI:
Lead Engineer: Ishimwe Lilas
Additive Current Data : Iradukunda Cherina, Itegineza Alvin
Economic Advisory: Igiraneza Charine
Organization: Nyehashi AI (Burundi)