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alwaysgood/Qwen3.5_4B_ADS
Qwen3.5_4B_ADS is a image-text-to-text model from alwaysgood. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
Qwen3.54BADS is a full fine-tune of unsloth/Qwen3.5-4B for English-to-Korean financial translation. It was trained with the DQS low-QE curriculum using seed 42.
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From the Hugging Face model README
Qwen3.5_4B_ADS is a full fine-tune of
unsloth/Qwen3.5-4B for
English-to-Korean financial translation. It was trained with the DQS
low-QE curriculum using seed 42.
This repository contains both the original Transformers checkpoint and one LM Studio/llama.cpp export:
model.safetensors: original BF16 fine-tuned checkpointQwen3.5_4B_ADS-Q4_K_M.gguf: the only quantized main-model variantmmproj-Qwen3.5_4B_ADS-BF16.gguf: vision encoder/projector companionThe BF16 mmproj is not an additional LLM quantization variant. It is kept at
BF16 for multimodal compatibility and quality.
Use the latest LM Studio runtime and download the Q4_K_M variant:
lms get https://huggingface.co/alwaysgood/Qwen3.5_4B_ADS@Q4_K_M
The matching mmproj file enables image input. For translation, disable
thinking and ask for translation-only output, for example:
Translate the following English financial text into Korean. Return only the translation.
<source text>
qe_selection_order=low)qwen35_4b_it_full_lowqe_seed42fa8166a883d96460cc285b46d66b74a074b4b8d4The checkpoint does not contain the optional Qwen3.5 MTP auxiliary head even though the inherited config declares one. The GGUF export therefore excludes MTP. Normal autoregressive generation is unaffected; MTP speculative decoding is not provided.
The following scores are from the original BF16 final checkpoint on the 500-row held-out test set. They are not claimed as a separate Q4_K_M evaluation.
| Metric | Score |
|---|---|
| BLEU | 27.4731 |
| chrF | 47.9918 |
COMET (wmt22-comet-da) | 0.8906 |
COMETKiwi (wmt22-cometkiwi-da) | 0.8565 |
| XCOMET-XXL | 0.8675 |
| MetricX-24 Hybrid XXL (lower is better) | 3.8712 |
Full evaluation records and configuration are available in the linked run.
The model weights follow the Apache-2.0 license of the base model. The training
corpus aggregates sources with mixed upstream terms; the dataset card is marked
license: other. Users are responsible for reviewing the source-specific terms
described in alwaysgood/financial-english-source-corpus.