Merged full model (bf16) of Qwen/Qwen3.6-35B-A3B with Slovenian fluency, knowledge, and en↔sl translation baked in (continued-pretraining + SFT). This is the LoRA adapter texdata/Qwen3.6-35B-A3B-Slovenian-LoRA already merged into the base, so you can load it directly. MTP (multi-token-prediction) tensors are preserved (model-mtp.safetensors) for speculative decoding.

On held-out evals vs the untuned base: Slovenian-LLM-Eval acc_norm 0.623 → 0.654; translation BLEU en→sl 23.8 → 26.3, sl→en 30.9 → 35.0. Reasoning model.

💡 For plug-and-play chat, a GGUF build (LM Studio / llama.cpp) is at texdata/Qwen3.6-35B-A3B-Slovenian-GGUF; the LoRA adapter alone is at texdata/Qwen3.6-35B-A3B-Slovenian-LoRA.

⚠️ How to run — load in 4-bit (not bf16)

This qwen3_5_moe arch has a broken fp16/bf16 forward in current transformers (zero hidden state → constant logits → garbage). Even though the weights here are bf16, load in 4-bit (bitsandbytes nf4) — the quantization it was trained/served under — or use the GGUF build. (vLLM does not run this arch on Blackwell sm_120 GPUs.)

python

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig

repo = "texdata/Qwen3.6-35B-A3B-Slovenian"
bnb  = BitsAndBytesConfig(load_in_4bit=True, bnb_4bit_quant_type="nf4",
                          bnb_4bit_compute_dtype=torch.bfloat16, bnb_4bit_use_double_quant=True)
tok   = AutoTokenizer.from_pretrained(repo, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(repo, quantization_config=bnb,
                                             trust_remote_code=True, device_map="auto")

# reasoning model: enable_thinking=False for direct answers/translation (else it spends tokens on <think>)
msg  = [{"role": "user", "content": "Prevedi v slovenščino: Good morning!"}]
text = tok.apply_chat_template(msg, add_generation_prompt=True, tokenize=False, enable_thinking=False)
out  = model.generate(**tok(text, return_tensors="pt").to(model.device), max_new_tokens=128)
print(tok.decode(out[0], skip_special_tokens=True))

Benchmarks

All numbers below use the 4-bit bnb (nf4) eval path — the quantization this model was trained/served under (see How to run; the native bf16 forward for this arch is broken). n=100/task, held-out. Random baseline ≈ 0.25–0.50.

Slovenian-LLM-Eval — acc_norm

Task	base Qwen3.6-35B-A3B	this model (CPT+SFT sl)	Δ
arc_easy	0.71	0.78	+0.07
arc_challenge	0.48	0.51	+0.03
hellaswag	0.59	0.62	+0.03
piqa	0.65	0.64	−0.01
openbookqa	0.48	0.51	+0.03
winogrande	0.62	0.63	+0.01
boolq	0.83	0.89	+0.06
AVERAGE	0.623	0.654	+0.031

Wins 6/7 tasks (+3.1 pts avg). Base at n=200 is consistent (0.614), so the gain is not a small-sample artifact; the piqa −1 is within n=100 noise (±~5 pts).

Translation — en↔sl BLEU / chrF (n=150 held-out OPUS, greedy, thinking off)

Direction	base Qwen3.6-35B-A3B	this model	Δ BLEU
en→sl	BLEU 23.79 / chrF 51.82	BLEU 26.26 / chrF 50.53	+2.47
sl→en	BLEU 30.85 / chrF 55.76	BLEU 34.95 / chrF 58.30	+4.10

Model details

Type: merged full model (bf16), MoE qwen3_5_moe (16 shards + model-mtp.safetensors).
Base: Qwen/Qwen3.6-35B-A3B (Apache-2.0, official — not an uncensored variant).
Adaptation: CPT + SFT LoRA (sft_qwen35a3b_sl) merged in; template: qwen. MTP preserved.

License & data provenance

Base Qwen/Qwen3.6-35B-A3B is Apache-2.0. CPT data is open-licensed (attribution applies) → this repo is license: other:

Data	License
Slovenian Wikipedia (CPT)	CC BY-SA 4.0 (attribution + ShareAlike)
FineWeb2 sl (CPT)	ODC-BY 1.0

Attribute the above. Comply with each source's terms before commercial use.

Citation

Cite this work (Tadej Fius, MediaAtlas Ltd):

bibtex

@misc{fius2026qwen35bsl,
  title        = {Qwen3.6-35B-A3B Slovenian (merged)},
  author       = {Fius, Tadej},
  year         = {2026},
  publisher    = {MediaAtlas Ltd},
  howpublished = {Hugging Face},
  url          = {https://huggingface.co/texdata/Qwen3.6-35B-A3B-Slovenian}
}

Upstream / source citations:

bibtex

@misc{qwen3, title={Qwen3 Technical Report}, author={{Qwen Team}}, year={2025}, url={https://huggingface.co/Qwen}}
@misc{wikipedia_sl, title={Slovenian Wikipedia}, author={{Wikimedia Foundation}}, note={CC BY-SA 4.0}, url={https://sl.wikipedia.org}}
@misc{penedo2024fineweb2, title={FineWeb2: A sparkling update with 1000s of languages}, author={Penedo, G. and others}, year={2024}, url={https://huggingface.co/datasets/HuggingFaceFW/fineweb-2}}

CPT data: Slovenian Wikipedia (CC BY-SA 4.0) and FineWeb2-sl (ODC-BY 1.0).