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---
license: apache-2.0
language:
- pl
- en
- multilingual
base_model:
- speakleash/Bielik-11B-v3.0-Instruct
library_name: mlx
pipeline_tag: text-generation
tags:
- mlx
- apple-silicon
- bielik
- polish
- bfloat16
- quantized
- bf16/fp16
inference: false
widget:
- text: Wyjaśnij krótko różnicę między diagnostyką różnicową a rozpoznaniem.
example_title: Polish instruction prompt
- text: Podsumuj najważniejsze ryzyka w planie wdrożenia.
example_title: Polish reasoning prompt
---
# Bielik-11B-v3.0-mlx-bf16
`Bielik-11B-v3.0-mlx-bf16` is an MLX BF16/FP16 packaging of `speakleash/Bielik-11B-v3.0-Instruct` for Polish and multilingual instruction-style generation on Apple Silicon.
## Intended use
- Local text generation and chat-style prompting on Apple Silicon
- MLX-LM experimentation with the declared upstream model family
- Offline or operator-controlled inference workflows
## Out of scope
- Safety-critical decisions without domain expert review
- Claims of benchmark superiority not backed by published evaluation data
- Non-MLX runtime guarantees; this card documents the shipped HF checkpoint, not every possible serving stack
## Training and conversion metadata
| Parameter | Value |
|---|---|
| Repository | `LibraxisAI/Bielik-11B-v3.0-mlx-bf16` |
| Base model | `speakleash/Bielik-11B-v3.0-Instruct` |
| Task | `text-generation` |
| Library | `mlx` |
| Format | MLX / Apple Silicon checkpoint |
| Quantization | BF16/FP16 |
| Architecture | LlamaForCausalLM |
| Model files | 5 |
| Config model_type | `llama` |
This card only reports metadata present in the Hugging Face repository, existing card frontmatter, or public config files. Missing benchmark, dataset, or training-run details are left explicit rather than reconstructed.
## Usage
### CLI
```bash
pip install mlx-lm
mlx_lm.generate \
--model LibraxisAI/Bielik-11B-v3.0-mlx-bf16 \
--prompt "Opisz krótko objawy odwodnienia u psa i kiedy pilnie skontaktować się z lekarzem weterynarii." \
--max-tokens 400
```
### Python
```python
from mlx_lm import load, generate
model, tokenizer = load("LibraxisAI/Bielik-11B-v3.0-mlx-bf16")
prompt = "Opisz krótko objawy odwodnienia u psa i kiedy pilnie skontaktować się z lekarzem weterynarii."
response = generate(model, tokenizer, prompt=prompt, max_tokens=400)
print(response)
```
### Multi-turn with the chat template
This checkpoint follows the tokenizer/chat-template contract inherited from `speakleash/Bielik-11B-v3.0-Instruct` when the
template is present in the repository:
```python
from mlx_lm import load, generate
model, tokenizer = load("LibraxisAI/Bielik-11B-v3.0-mlx-bf16")
messages = [
{"role": "user", "content": "Opisz krótko objawy odwodnienia u psa i kiedy pilnie skontaktować się z lekarzem weterynarii."},
]
prompt = tokenizer.apply_chat_template(messages, add_generation_prompt=True, tokenize=False)
response = generate(model, tokenizer, prompt=prompt, max_tokens=400)
print(response)
```
## Example output
No public sample output is currently declared for this checkpoint. Run the usage example above against your own prompt or audio/image input to inspect behavior.
## Quantization notes
| Aspect | Original/base checkpoint | This checkpoint |
|---|---|---|
| Lineage | `speakleash/Bielik-11B-v3.0-Instruct` | `LibraxisAI/Bielik-11B-v3.0-mlx-bf16` |
| Runtime target | Upstream runtime format | MLX on Apple Silicon |
| Quantization | Base precision or upstream-declared format | BF16/FP16 |
| Published quality delta | Not declared in public metadata | Not declared in public metadata |
## Limitations
- No public benchmarks for this checkpoint are declared in the model metadata.
- No public benchmark claims are made by this card unless listed in the frontmatter.
- Validate outputs on your own domain data before relying on this checkpoint.
- Memory use and speed depend heavily on the exact Apple Silicon generation, unified-memory size, and prompt length.
## License
`apache-2.0`. Check the upstream/base model license as well when a base model is declared.
## Citation
```bibtex
@misc{libraxisai-bielik-11b-v3-0-mlx-bf16,
title = {Bielik-11B-v3.0-mlx-bf16},
author = {LibraxisAI},
year = {2026},
howpublished = {\url{https://huggingface.co/LibraxisAI/Bielik-11B-v3.0-mlx-bf16}},
note = {MLX checkpoint published by LibraxisAI}
}
```
## Inference tested on
[`LibraxisAI/mlx-batch-server`](https://github.com/LibraxisAI/mlx-batch-server)
## Related
- Base model: [`speakleash/Bielik-11B-v3.0-Instruct`](https://huggingface.co/speakleash/Bielik-11B-v3.0-Instruct)
---
𝚅𝚒𝚋𝚎𝚌𝚛𝚊𝚏𝚝𝚎𝚍. with AI Agents by VetCoders (c)2024-2026 LibraxisAI