[whatmodel.sh](../../README.md) / Bielik 1.5B v3.0 Instruct # Bielik 1.5B v3.0 Instruct SpeakLeash · released 2025-04 · 1.6B params · apache-2.0 **score 41.2** ±2.8 · #544 of 732 · from 3 benchmark results across 2 sources Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only. ## What it's good at ● marks Bielik 1.5B v3.0 Instruct among every model on that task or test, worst to best.
test result vs the others in its run difficulty counts why CPTUB average (SpeakLeash, 0-5 ju… 47.3% ▁▂▂●▃█▃▆▅▄▂▃ beats 15/95 medium · avg 65% 68% at its level EuroEval HellaSwag (English), tes… 50.6% ▃·▁▁▂▁●▅█▇▄▁ beats 27/100 medium · avg 67% 14% sharp · at its level · noisy EuroEval Life in the UK (English … 71.8% ▁▁▁▁▁▁▁▂●█▄▃ beats 41/146 easy · avg 82% 14% at its level · noisy
source results share of the score SpeakLeash CPTUB (submitted / maker-rep… 1 68% ▇▇▇▇▇▇▇▇ EuroEval leaderboards 2 28% ▇▇▇ prior: pull toward the middle 4% ▇ weighted average = 41.2Licences: SpeakLeash CPTUB ([MIT](../../licenses/hf-leaderboard-spaces-MIT.txt)) · EuroEval leaderboards ([MIT](https://github.com/EuroEval/leaderboards/blob/1a77f1d2f8ba1ba05ab73287fb090d76bf41b2e0/LICENSE)) ## How to run it ### llama.cpp (recommended) 1. Install llama.cpp. Homebrew and winget installs name the commands llama-cli and llama-server instead. [Other ways to install](https://github.com/ggml-org/llama.cpp/blob/master/docs/install.md) ```sh # macOS / Linux curl -LsSf https://llama.app/install.sh | sh # Windows irm https://llama.app/install.ps1 | iex ``` 2. Run Bielik 1.5B v3.0 Instruct (Q4_K_M, needs ~1 GB, from [huggingface.co/second-state](https://huggingface.co/second-state/Bielik-1.5B-v3.0-Instruct-GGUF/tree/6c316d2be07dee472901150c3f3e9d4f725a4706)) ```sh llama cli -hf second-state/Bielik-1.5B-v3.0-Instruct-GGUF:Q4_K_M ``` 3. Or start a local server and open the address it prints (http://localhost:9931) ```sh llama serve -hf second-state/Bielik-1.5B-v3.0-Instruct-GGUF:Q4_K_M ``` Other versions: Q8_0 (~1.7 GB) `llama cli -hf second-state/Bielik-1.5B-v3.0-Instruct-GGUF:Q8_0` ### LM Studio 1. Install LM Studio. Open the app once before using the lms command. [Download it (macOS / Windows / Linux)](https://lmstudio.ai/download) 2. Run Bielik 1.5B v3.0 Instruct (Q4_K_M, needs ~1 GB, from [huggingface.co/second-state](https://huggingface.co/second-state/Bielik-1.5B-v3.0-Instruct-GGUF/tree/6c316d2be07dee472901150c3f3e9d4f725a4706)) ```sh lms get https://huggingface.co/second-state/Bielik-1.5B-v3.0-Instruct-GGUF@Q4_K_M -y ``` 3. Then run lms ls to see its name, and lms chat followed by that name Other versions: Q8_0 (~1.7 GB) `lms get https://huggingface.co/second-state/Bielik-1.5B-v3.0-Instruct-GGUF@Q8_0 -y` · 4bit (~0.9 GB, Mac only) `lms get https://huggingface.co/futurist-ai/Bielik-1.5B-v3.0-Instruct-MLX-4bit -y` · 8bit (~1.7 GB, Mac only) `lms get https://huggingface.co/speakleash/Bielik-1.5B-v3.0-Instruct-MLX-8bit -y` ### Ollama 1. Install Ollama. [Download it (macOS / Windows)](https://ollama.com/download) ```sh # Linux curl -fsSL https://ollama.com/install.sh | sh ``` 2. Run Bielik 1.5B v3.0 Instruct (Q4_K_M, needs ~1 GB, from [huggingface.co/second-state](https://huggingface.co/second-state/Bielik-1.5B-v3.0-Instruct-GGUF/tree/6c316d2be07dee472901150c3f3e9d4f725a4706)) ```sh ollama run hf.co/second-state/Bielik-1.5B-v3.0-Instruct-GGUF:Q4_K_M ``` Other versions: Q8_0 (~1.7 GB) `ollama run hf.co/second-state/Bielik-1.5B-v3.0-Instruct-GGUF:Q8_0` ### MLX (Mac) 1. Install MLX (Mac). Apple silicon Macs only, text only. ```sh # with uv uv tool install mlx-lm # or pip install mlx-lm ``` 2. Run Bielik 1.5B v3.0 Instruct (4bit, needs ~0.9 GB, Mac only, from [huggingface.co/futurist-ai](https://huggingface.co/futurist-ai/Bielik-1.5B-v3.0-Instruct-MLX-4bit/tree/77f20f0033c7b02bb3b0c8064511700d7782cda0)) ```sh mlx_lm.chat --model futurist-ai/Bielik-1.5B-v3.0-Instruct-MLX-4bit ``` 3. Or start an OpenAI-compatible server at http://localhost:8080/v1 ```sh mlx_lm.server --model futurist-ai/Bielik-1.5B-v3.0-Instruct-MLX-4bit ``` Other versions: 8bit (~1.7 GB, Mac only) `mlx_lm.chat --model speakleash/Bielik-1.5B-v3.0-Instruct-MLX-8bit` ### Other ways to run it 1. Run it as published (BF16, needs ~3.19 GB, from [huggingface.co/speakleash](https://huggingface.co/speakleash/Bielik-1.5B-v3.0-Instruct/tree/1907cec498b762e8223b7cffc2b8f279c417a44d)) ```sh uv run --with torch --with 'transformers<5' --with accelerate python -c "from transformers import pipeline; print(pipeline('text-generation', model='speakleash/Bielik-1.5B-v3.0-Instruct', torch_dtype='auto', device_map='auto')('Once upon a time', max_new_tokens=40)[0]['generated_text'])" ``` Model repository and documentation: [huggingface.co/speakleash](https://huggingface.co/speakleash/Bielik-1.5B-v3.0-Instruct) [interactive version](https://whatmodel.sh/model/bielik-1-5b-v3-0-instruct) · [JSON](https://whatmodel.sh/api?format=json&all=1)