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nbeerbower/Huihui-Qwen3.5-9B-abliterated-TIES

nbeerbower Qwen 9.7B multimodal
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  • classification m5
  • files 14
  • hub_downloads_all_time 123
  • author_summary 27 models
  • readme_text full
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Abliteration classifier · v1.0.0
M5
Primary method

Mergekit merge

Applied on top of direct removal inherited from the base model.
Confidence
MEDIUM
Inherited from base model
Why this label 3 signals
Method inferred from partial signals - repository name, related files, or tag patterns. Producer identity not confirmed; label may sharpen or shift as we gather more evidence.
  • merge tag / mergekit / dare-ties in tags or name
  • no unusual architecture pattern (regular merge)
  • abliterated marker present
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No specific extraction method could be identified for this model. The producer either did not document it or used a proprietary pipeline.

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Downloads · lifetime
123
28 last 30d - stable
Likes
1
Descendants
6
in 3 direct forks
Model age
6mo ago
created 2026-03-24
Downloads over time
Now135→from14↑864%
85410114714 on Mar 25135 on Oct 11MarAprMayJunJulAugSepOct
Mar 25 → Oct 11 · 68 snapshots · spans 200 days

Genealogy 3 direct forks

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Metadata

Tags
transformers safetensors qwen3_5 image-text-to-text mergekit merge conversational arxiv:2306.01708 base_model:Qwen/Qwen3.5-9B-Base base_model:merge:Qwen/Qwen3.5-9B-Base base_model:huihui-ai/Huihui-Qwen3.5-9B-abliterated base_model:merge:huihui-ai/Huihui-Qwen3.5-9B-abliterated

Related

Total size
18.0 GB
Files
14
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-03-24 18:19

Files by quantization

Auxiliary files 14 files 18.1 GB
model-00002-of-00004.safetensors 4.65 GB d847cb47 download
model-00003-of-00004.safetensors 4.61 GB 93ebd27c download
model-00001-of-00004.safetensors 4.60 GB 4f3a56c3 download
model-00004-of-00004.safetensors 2.88 GB 9f9b805c download
model-vlm.safetensors 1.30 GB 21cbc389 download
tokenizer.json 12.2 MB fe000e3e download
model.safetensors.index.json 65.0 KB e88f8a04 download
tokenizer_config.json 16.3 KB ae8d254e download
config.json 3.05 KB 273ce437 download
README.md 2.85 KB fe09f422 download
.gitattributes 1.53 KB 52373fe2 download
mergekit_config.yml 465 B 434a55b0 download
preprocessor_config.json 390 B 2ea84a43 download
video_preprocessor_config.json 386 B 37900b3f download

README current version from Hugging Face


base_model:

  • Qwen/Qwen3.5-9B-Base
  • nbeerbower/Huihui-Qwen3.5-9B-abliterated-Grimoire-SFT
  • nbeerbower/Huihui-Qwen3.5-9B-abliterated-Grimoire-ORPO
  • huihui-ai/Huihui-Qwen3.5-9B-abliterated
    library_name: transformers
    tags:
  • mergekit
  • merge

Huihui-Qwen3.5-9B-abliterated-TIES

This is a merge of pre-trained language models created using a custom fork of mergekit with Qwen3.5 architecture support.

Merge Details

Merge Method

This model was merged using the TIES merge method using Qwen/Qwen3.5-9B-Base as a base.

Models Merged

The following models were included in the merge:

Mergekit Changes for Qwen3.5

Qwen3.5 uses a hybrid attention architecture (3:1 linear/full attention layers) that mergekit does not yet support upstream. The following changes were made to enable this merge:

  1. New architecture definitions (qwen3_5.json, qwen3_5_text.json) - Defines tensor mappings for both Qwen3_5ForConditionalGeneration (VLM) and Qwen3_5ForCausalLM (text-only) architectures. The hybrid self_attn and linear_attn layer weights are marked as optional since they only appear on specific layers (full attention every 4th layer, linear attention on the rest).

  2. Config key fallback (mergekit/common.py) - Added a fallback in get_config_value so that nested config keys like text_config.num_hidden_layers gracefully resolve to num_hidden_layers on text-only model configs. This enables cross-architecture merges between VLM and text-only Qwen3.5 variants.

  3. Vision weight grafting - The SFT and ORPO fine-tuned models are text-only (Qwen3_5ForCausalLM) and lack the vision encoder. After the text merge, the vision encoder (model.visual.*) and MTP head (mtp.*) weights were grafted from the base VLM model (Qwen/Qwen3.5-9B-Base) to produce a complete VLM.

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: huihui-ai/Huihui-Qwen3.5-9B-abliterated
    parameters:
      weight: 0.4
      density: 0.6
  - model: nbeerbower/Huihui-Qwen3.5-9B-abliterated-Grimoire-SFT
    parameters:
      weight: 0.3
      density: 0.6
  - model: nbeerbower/Huihui-Qwen3.5-9B-abliterated-Grimoire-ORPO
    parameters:
      weight: 0.5
      density: 0.6
merge_method: ties
base_model: Qwen/Qwen3.5-9B-Base
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16

README history 1 version

The author's README evolved over time. Click a version to see its content at that point.

  1. 2026-03-24Upload folder using huggingface_hub05785262.8 KB
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