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Model Details
Model Provider
groxaxo
Model Tree
ConicCat/Qwen3.5-27B-Writer-V2
groxaxo/Qwen3.5-27B-Writer-V2-Heretic-Coding-LoRA
Input Modalities
Output Modalities
Supported Functionality
Qwevolution-V0-27B is a model checkpoint packaged for compatible Hugging Face runtimes, published by groxaxo.
It is intended for open-source evaluation, reproducible experimentation, and compatible local or
hosted inference workflows. The wording below is deliberately limited to what can be verified
from this repository's metadata and artifacts.
| Field | Details |
|---|---|
| Format | Transformers |
| Source / base | ConicCat/Qwen3.5-27B-Writer-V2 |
| Intended task | image-text-to-text |
| License | apache-2.0 |
*.safetensors (12 files)config.jsongeneration_config.jsontokenizer.jsontokenizer_config.jsonprocessor_config.jsonchat_template.jinjaStart with the upstream library named in the repository metadata and keep all configuration, tokenizer, processor, and weight files together. This repository is an artifact release, so the source project remains the authoritative reference for task-specific loading code.
Generated outputs may be inaccurate or unsuitable for a given use case. Users are responsible for testing behavior, applying appropriate safeguards, and complying with applicable licenses and laws.
A weight-space blend of the ConicCat/Qwen3.5-27B-Writer-V2 vision-language model with the
groxaxo/Qwen3.5-27B-Writer-V2-Heretic-Coding-LoRA coding LoRA adapter, merged with peft.merge_and_unload(safe_merge=True) in bfloat16.
Qwen3_5ForConditionalGeneration, 27B, BF16, license apache-2.0. Base commit 55f457bed78b68442d25815bd156b98f2e6fd341.0b3508764f80741f612c251c7f47b1e210ac2e63.Deliberate cross-base merge. The coding LoRA was originally trained on
llmfan46/Qwen3.5-27B-Writer-V2-uncensored-heretic. It was intentionally merged onto the cleanConicCat/Qwen3.5-27B-Writer-V2(same Writer-V2 lineage / identical architecture, vocab and module tree).
The adapter touched 607 modules. Of these, 496 language-tower modules carried trained
(non-zero) weights and were merged into the base. The remaining 111 vision-tower modules were
zero in the adapter itself (never trained) — merging them is a no-op, so the vision tower is
identical to the base model and vision behaviour should match ConicCat/Qwen3.5-27B-Writer-V2.
safe_merge=True (per-layer NaN check).B).merge_manifest.json for exact base/adapter commits and library versions.python
from transformers import AutoModelForImageTextToText, AutoProcessormodel = AutoModelForImageTextToText.from_pretrained("groxaxo/Qwevolution-V0-27B", dtype="bfloat16", device_map="auto")processor = AutoProcessor.from_pretrained("groxaxo/Qwevolution-V0-27B")