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ornith-1.5-9b-uncensored
# Ornith-1.5-9B-uncensored
An **abliterated** (refusal-direction-ablated) build of
`ornith-ai/Ornith-1.5-9B`, produced with
ZeroFuse and published by
junafinity.
This is the **9B control checkpoint** (bf16). Mac users should start from the MLX-8bit or GGUF-8bit siblings. The official 9B base has **no `mtp.*` tensors**; nothing was grafted.
**Vision tower and MTP heads are preserved** — see
Vision & MTP preservation for the before/after audit.
## Intended use: red teaming and defensive cybersecurity research
These uncensored (abliterated) weights are built as a **research instrument** for red teaming and defensive cybersecurity work. Safety training suppresses the *display* of capability, not capability itself. A refusal tells you the model declined. It does not tell you whether the weights could have complied. That conflation underestimates the true ceiling and hides holes in *your* filters, classifiers, and policy layer.
Use each uncensored checkpoint as the **treatment half of a controlled pair** against its original base model:
...
Repository: localaiLicense: apache-2.0
Attention: Trust Remote Code is required for this model
wemm-embedding-9b
WeMM-Embedding-9B is Tencent's largest Apache-2.0 multilingual embedding
model built on Qwen3.5. This entry serves the original bfloat16 safetensors
with LocalAI's Transformers backend and produces 4,096-dimensional
normalized embeddings for text retrieval, semantic search, and RAG.
The upstream model can also embed images and videos. LocalAI currently
exposes text input through its embeddings API for this backend.
Repository: localaiLicense: apache-2.0
ornith-1.0-9b-q4
Ornith-1.0-9B is an MIT-licensed Qwen3.5 model from Ornith AI for
agentic coding, reasoning, repository-level software tasks, and tool use.
It supports text and image input with a context window of 262K tokens.
This default entry uses the Q4_K_M GGUF and F16 vision projector. A
higher-quality Q8_0 model is available as a variant.
Repository: localaiLicense: mit
ornith-1.0-9b-q8
Ornith-1.0-9B in the higher-quality Q8_0 GGUF format, with the shared F16
vision projector for multimodal prompts.
Repository: localaiLicense: mit
ornith-1.5-9b-q4
Ornith-1.5-9B is an MIT-licensed Qwen3.5 model from Ornith AI for
agentic coding, reasoning, repository-level software tasks, and tool use.
It supports text and image input with a context window of 262K tokens.
This default entry uses the Q4_K_M GGUF and BF16 vision projector.
Q5_K_M, Q6_K, and Q8_0 models are available as variants.
Repository: localaiLicense: mit
ornith-1.5-9b-q5
Ornith-1.5-9B in the Q5_K_M GGUF format, with the shared BF16
vision projector for multimodal prompts.
Repository: localaiLicense: mit
ornith-1.5-9b-q6
Ornith-1.5-9B in the Q6_K GGUF format, with the shared BF16
vision projector for multimodal prompts.
Repository: localaiLicense: mit
ornith-1.5-9b-q8
Ornith-1.5-9B in the higher-quality Q8_0 GGUF format, with the shared BF16
vision projector for multimodal prompts.
Repository: localaiLicense: mit
ornith-1.5-9b-uncensored-q4
Junafinity's Ornith-1.5-9B Uncensored is a 9B-parameter Qwen3.5
derivative with refusal-direction ablation for research and evaluation.
This Q4_K_M GGUF build includes the F16 vision projector and uses
the embedded chat template for text and image conversations.
Repository: localaiLicense: apache-2.0
ornith-1.5-9b-uncensored-q6
Junafinity's Ornith-1.5-9B Uncensored is a 9B-parameter Qwen3.5
derivative with refusal-direction ablation for research and evaluation.
This Q6_K GGUF build includes the F16 vision projector and uses
the embedded chat template for text and image conversations.
Repository: localaiLicense: apache-2.0
ornith-1.5-9b-uncensored-q8
Junafinity's Ornith-1.5-9B Uncensored is a 9B-parameter Qwen3.5
derivative with refusal-direction ablation for research and evaluation.
This Q8_0 GGUF build includes the F16 vision projector and uses
the embedded chat template for text and image conversations.
Repository: localaiLicense: apache-2.0
ornith-1.5-9b-obliterated-q4
Ornith-1.5-9B OBLITERATED is a refusal-removed derivative for alignment
research, red teaming, coding, reasoning, and agentic tasks. Its safety
guardrails are removed, and the publisher reports some capability loss
compared with the original model.
This default entry uses the Q4_K_M GGUF and BF16 vision projector. The
linked variant uses the higher-quality Q8_0 quantization.
Repository: localaiLicense: mit
ornith-1.5-9b-obliterated-q8
Ornith-1.5-9B OBLITERATED in the higher-quality Q8_0 GGUF format, with the
shared BF16 vision projector. Its safety guardrails are removed, and the
publisher recommends this quantization for better behavior fidelity.
Repository: localaiLicense: mit
qwen3.8-9b-q4
Qwen3.8-9B is Empero AI's full-parameter distillation of Qwen3.8 2.4T
A95B into the dense Qwen3.5-9B architecture. It targets reasoning,
mathematics, coding, instruction following, and tool use, and supports a
native 262K-token context window. This default entry uses Q4_K_M weights;
a higher-quality Q8_0 build is available as a variant.
Repository: localaiLicense: apache-2.0
qwen3.8-9b-q8
Qwen3.8-9B in the higher-quality Q8_0 GGUF format. This variant preserves
more model fidelity for hosts with enough memory.
Repository: localaiLicense: apache-2.0
qwen3.5-9b-defiant-fable-mtp
Qwen3.5 9B Defiant Fable is an Apache-2.0 multimodal fine-tune for
reasoning, coding, creative writing, and roleplay. It retains the 256K
context window and vision support of Qwen3.5 while reducing refusals.
This default entry uses the NEO-imatrix Q4_K_M build with multi-token
prediction enabled for faster generation.
Repository: localaiLicense: apache-2.0
qwen3.5-9b-defiant-fable
Qwen3.5 9B Defiant Fable in the plain NEO-imatrix Q4_K_M GGUF format.
This fallback offers the same multimodal reasoning, coding, and creative
capabilities without enabling multi-token prediction.
Repository: localaiLicense: apache-2.0
qwen3.5-9b-defiant-fable-q8-mtp
Qwen3.5 9B Defiant Fable in Q8_0 GGUF format for multimodal reasoning,
coding, and creative writing. Includes the matching BF16 vision projector.
Enables multi-token prediction with the MTP weights.
Repository: localaiLicense: apache-2.0
qwen3.5-9b-defiant-fable-q8
Qwen3.5 9B Defiant Fable in Q8_0 GGUF format for multimodal reasoning,
coding, and creative writing. Includes the matching BF16 vision projector.
Uses ordinary decoding without multi-token prediction.
Repository: localaiLicense: apache-2.0
qwen3.8-9b-distill-q4
Qwen3.8 9B Distill is an Apache-2.0, text-only Qwen3.5 9B fine-tune
distilled from Qwen3.8 2.4T A95B reasoning traces. It targets mathematics,
coding, instruction following, and function calling with a 262K native
context window. This entry uses the balanced Q4_K_M GGUF quantization; the
Q8_0 variant offers higher fidelity.
Repository: localaiLicense: apache-2.0
qwen3.8-9b-distill-q8
Qwen3.8 9B Distill in the higher-fidelity Q8_0 GGUF format. This text-only
Qwen3.5 9B fine-tune targets reasoning, coding, instruction following, and
function calling with a 262K native context window.
Repository: localaiLicense: apache-2.0
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