Text Generation
MLX
Safetensors
Swahili
English
llama
swahili
tanzania
bilingual
natural-language-processing
conversational
Instructions to use Bur3hani/MuchKnow-Swahili-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use Bur3hani/MuchKnow-Swahili-8B with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("Bur3hani/MuchKnow-Swahili-8B") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use Bur3hani/MuchKnow-Swahili-8B with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "Bur3hani/MuchKnow-Swahili-8B"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "Bur3hani/MuchKnow-Swahili-8B" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Bur3hani/MuchKnow-Swahili-8B", "messages": [ {"role": "user", "content": "Hello"} ] }' - Atomic Chat
MuchKnow-Swahili-8B 🇹🇿🇬🇧
MuchKnow-Swahili-8B is a high-performance bilingual (Tanzanian Kiswahili 🇹🇿 + English 🇬🇧) Large Language Model fine-tuned on top of deepseek-ai/DeepSeek-R1-Distill-Llama-8B.
Developed for MuchKnow (muchknow.com) and copyrighted to BuruOps (buruops.com), this model understands and generates authentic East African Kiswahili across three distinct linguistic registers alongside fluent English.
🌟 Key Features
- Triple Kiswahili Register Alignment (Sajili Tatu za Kiswahili):
- Kiswahili Sanifu (Standard Swahili): Formal communication, official correspondence, and educational contexts based on BAKITA standards.
- Kiswahili Fasaha (Refined / Literary Swahili): Sophisticated, grammatically rich, and expressive Swahili suitable for literature, speeches, and deep technical discourse.
- Kiswahili cha Mtaani (Street Swahili / Sheng): Authentic urban street vernacular used across Tanzanian cities (Dar es Salaam, Arusha, Mwanza, Dodoma) for natural conversational engagement.
- Native English & Kiswahili Code-Switching:
- Seamlessly comprehends queries in English, Kiswahili, or mixed bilingual inputs, and responds in the user's preferred language.
- Advanced Reasoning:
- Inherits DeepSeek-R1's strong mathematical, logic, and reasoning capabilities distilled into an efficient 8B parameter model.
🚀 Quickstart Usage
Using mlx_lm (Apple Silicon Mac)
from mlx_lm import load, generate
model, tokenizer = load("Bur3hani/MuchKnow-Swahili-8B")
prompt = """Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
Eleza kwa Kiswahili Sanifu na Kiswahili cha Mtaani jinsi ya kuanzisha biashara ya mtandaoni nchini Tanzania.
### Response:
"""
response = generate(model, tokenizer, prompt=prompt, max_tokens=512)
print(response)
📜 Copyright & License
- Copyright: © 2026 BuruOps (buruops.com) & MuchKnow (muchknow.com). All Rights Reserved.
- Base Model License: [Apache 2.0 / MIT] derived from DeepSeek-R1-Distill-Llama-8B.
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Model size
8B params
Tensor type
BF16
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Hardware compatibility
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Base model
deepseek-ai/DeepSeek-R1-Distill-Llama-8B