Instructions to use arnastofnun/Qwen3-4B-wmt26-AMI-en-is-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use arnastofnun/Qwen3-4B-wmt26-AMI-en-is-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("./merged_qwen3_4b_icelandic") model = PeftModel.from_pretrained(base_model, "arnastofnun/Qwen3-4B-wmt26-AMI-en-is-lora") - Transformers
How to use arnastofnun/Qwen3-4B-wmt26-AMI-en-is-lora with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="arnastofnun/Qwen3-4B-wmt26-AMI-en-is-lora")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("arnastofnun/Qwen3-4B-wmt26-AMI-en-is-lora", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Qwen3-4B-wmt26-AMI-en-is-lora
A LoRA adapter fine-tuning
arnastofnun/Qwen3-4B-wmt26-AMI-en-is
(a mergekit blend of Qwen/Qwen3-4B-Instruct-2507 with a continually
pretrained Icelandic checkpoint) for English→Icelandic machine
translation, trained with Unsloth.
Built by Árnastofnun (The Árni Magnússon Institute for Icelandic Studies) as part of the AMI submission to the WMT 2026 General Translation shared task.
Model description
The base checkpoint was continually pretrained on Icelandic data from the Icelandic Gigaword Corpus (IGC) before this LoRA fine-tune was applied (see the base model card for the merge details).
Fine-tuned on a retrieval-augmented (RAG) prompt format: each training example pairs a domain-specific system prompt (general, news, social, software, or speech) with a user turn containing retrieved bilingual dictionary entries and similar example translations for the source sentence, and an assistant turn with the reference Icelandic translation. Loss is computed over the assistant turn only. Trained on 4,996 examples across the five domains above.
Training data
stofnun-arna-magnussonar/WMT2026_finetuning_dataset
— wmt26_translate_train.jsonl, the combined ChatML SFT dataset (4,996
examples), with an explanation of how it was built (RAG-retrieved
dictionary hits and example translations from the Icelandic Gigaword
Corpus, assembled alongside WMT24/25 EN-IS test data and synthetically
generated pairs).
At inference time, source sentences must go through the same retrieval/prompt-construction pipeline used in training — this adapter expects dictionary hits and example translations in the prompt context, not a bare source sentence.
Training hyperparameters
| LoRA rank | 16 |
| LoRA alpha | 16 |
| LoRA dropout | 0 |
| Target modules | q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj |
| Max sequence length | 8192 |
| Framework | Unsloth + PEFT 0.19.1 |
Uses
Serve the base model with the adapter attached, e.g. with vLLM:
vllm serve arnastofnun/Qwen3-4B-wmt26-AMI-en-is \
--enable-lora \
--lora-modules translate-lora=arnastofnun/Qwen3-4B-wmt26-AMI-en-is-lora
Or load directly with PEFT:
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
base = AutoModelForCausalLM.from_pretrained("arnastofnun/Qwen3-4B-wmt26-AMI-en-is")
model = PeftModel.from_pretrained(base, "arnastofnun/Qwen3-4B-wmt26-AMI-en-is-lora")
tokenizer = AutoTokenizer.from_pretrained("arnastofnun/Qwen3-4B-wmt26-AMI-en-is-lora")
Out-of-scope use
Not intended for language pairs or directions other than English→Icelandic, and expects RAG-style context (dictionary/example retrieval) in its prompts — quality without that context is not evaluated.
Citation
If you use this model, please cite:
@inproceedings{steingrimsson2026drag,
title = {What a DRAG (It Is Being Small) - The AMI Submission to the WMT 2026 General Translation Shared Task},
author = {Steingr{\'i}msson, Stein{\th}{\'o}r and {\TH}{\'o}r{\dh}arson, Sveinbj{\"o}rn and Da{\dh}ason, J{\'o}n Fri{\dh}rik},
booktitle = {Proceedings of the Eleventh Conference on Machine Translation},
month = oct,
year = {2026},
address = {Budapest, Hungary},
publisher = {Association for Computational Linguistics}
}
Framework versions
- PEFT 0.19.1
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Model tree for arnastofnun/Qwen3-4B-wmt26-AMI-en-is-lora
Base model
Qwen/Qwen3-4B-Instruct-2507