HuggingFaceFW/fineweb-2
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How to use bogdanminko/RuadaptQwen3-4B-Instruct-MLX-8bit 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("bogdanminko/RuadaptQwen3-4B-Instruct-MLX-8bit")
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)How to use bogdanminko/RuadaptQwen3-4B-Instruct-MLX-8bit with Pi:
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "bogdanminko/RuadaptQwen3-4B-Instruct-MLX-8bit"
# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
"providers": {
"mlx-lm": {
"baseUrl": "http://localhost:8080/v1",
"api": "openai-completions",
"apiKey": "none",
"models": [
{
"id": "bogdanminko/RuadaptQwen3-4B-Instruct-MLX-8bit"
}
]
}
}
}# Start Pi in your project directory: pi
How to use bogdanminko/RuadaptQwen3-4B-Instruct-MLX-8bit with Hermes Agent:
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "bogdanminko/RuadaptQwen3-4B-Instruct-MLX-8bit"
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default bogdanminko/RuadaptQwen3-4B-Instruct-MLX-8bit
hermes
How to use bogdanminko/RuadaptQwen3-4B-Instruct-MLX-8bit with MLX LM:
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "bogdanminko/RuadaptQwen3-4B-Instruct-MLX-8bit"
# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "bogdanminko/RuadaptQwen3-4B-Instruct-MLX-8bit"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "bogdanminko/RuadaptQwen3-4B-Instruct-MLX-8bit",
"messages": [
{"role": "user", "content": "Hello"}
]
}'This model Bogdan01m/RuadaptQwen3-4B-Instruct-MLX-8bit was converted to MLX format from RefalMachine/RuadaptQwen3-4B-Instruct using mlx-lm version 0.28.3.
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("Bogdan01m/RuadaptQwen3-4B-Instruct-MLX-8bit")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)
@article{tikhomirov2024facilitating,
title={Facilitating Large Language Model Russian Adaptation with Learned Embedding Propagation},
author={Tikhomirov, Mikhail and Chernyshov, Daniil},
journal={Journal of Language and Education},
volume={10},
number={4},
pages={130--145},
year={2024}
}
8-bit
Base model
Qwen/Qwen3-4B-Instruct-2507