Instructions to use speakleash/Bielik-1.5B-v3.0-Instruct-MLX-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use speakleash/Bielik-1.5B-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-1.5B-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) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use speakleash/Bielik-1.5B-v3.0-Instruct-MLX-8bit with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "speakleash/Bielik-1.5B-v3.0-Instruct-MLX-8bit"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "speakleash/Bielik-1.5B-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-1.5B-v3.0-Instruct-MLX-8bit", "messages": [ {"role": "user", "content": "Hello"} ] }'
Bielik-1.5B-v3.0-Instruct-MLX-8bit
This model was converted to MLX format from SpeakLeash's Bielik-1.5B-v3.0-Instruct.
DISCLAIMER: Be aware that quantised models show reduced response quality and possible hallucinations!
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("speakleash/Bielik-1.5B-v3.0-Instruct-MLX-8bit")
response = generate(model, tokenizer, prompt="hello", verbose=True)
Model description:
- Developed by: SpeakLeash & ACK Cyfronet AGH
- Language: Polish
- Model type: causal decoder-only
- Quant from: Bielik-1.5B-v3.0-Instruct
- Finetuned from: Bielik-1.5B-v3
- License: Apache 2.0 and Terms of Use
Responsible for model quantization
- Remigiusz KinasSpeakLeash - team leadership, conceptualizing, calibration data preparation, process creation and quantized model delivery.
Contact Us
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Model size
0.4B params
Tensor type
F16
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U32 ·
Hardware compatibility
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8-bit
Model tree for speakleash/Bielik-1.5B-v3.0-Instruct-MLX-8bit
Base model
speakleash/Bielik-1.5B-v3 Finetuned
speakleash/Bielik-1.5B-v3.0-Instruct