Bielik-v3 - Family
Collection
Bielik-v3 model family - models in all sizes and quantizations • 15 items • Updated • 30
How to use speakleash/Bielik-11B-v3.0-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("speakleash/Bielik-11B-v3.0-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 speakleash/Bielik-11B-v3.0-Instruct-MLX-8bit with MLX LM:
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "speakleash/Bielik-11B-v3.0-Instruct-MLX-8bit"
# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "speakleash/Bielik-11B-v3.0-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": "speakleash/Bielik-11B-v3.0-Instruct-MLX-8bit",
"messages": [
{"role": "user", "content": "Hello"}
]
}'
This model was converted to MLX format from SpeakLeash's Bielik-11B-v3.0-Instruct.
DISCLAIMER: Be aware that quantised models show reduced response quality and possible hallucinations!
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("speakleash/Bielik-11B-v3.0-Instruct-MLX-8bit")
response = generate(model, tokenizer, prompt="hello", verbose=True)
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8-bit
Base model
speakleash/Bielik-11B-v3-Base-20250730