Ornith-1.5-9B-uncensored
9BOrnithuncensored
from ornith-ai/Ornith-1.5-9B
↓ 1.8M♥ 26929 repos
Ornith-1.5-122B-UNCENSORED
Ornith-1.5-122B-UNCENSORED is a abliterated and uncensored variant of ornith-ai/Ornith-1.5-122B, published on Hugging Face by dealignai. It is 122B parameters, server-class deployment class and mit licence. It is distributed across 5 repositories in GGUF and NVFP4 formats, totalling 38.2K downloads.
Specification
- Model name
- Ornith-1.5-122B-UNCENSORED
- Source repository
- dealignai/Ornith-1.5-122B-UNCENSORED-GGUF
- Base model
- ornith-ai/Ornith-1.5-122B
- Publisher
- dealignai
- Parameters
- 122B
- VRAM required
- ~74.7 GB at Q4_K_M, 4k context (estimated) — runs on 80 GB cards
- Hardware class
- 100B+ — server-class deployment
- Licence
- mit
- Task
- Text generation
- Context window
- 4K tokens (as documented)
- Ablation scope
- Not stated by the publisher
- Formats available
- GGUF, NVFP4
- First indexed
- 19 Oct 2026
- Last updated
- 28 Oct 2026
Ablation technique
How Ornith-1.5-122B-UNCENSORED was modified, and what that implies.
Abliteration + uncensored fine-tune
Directional ablation combined with additional fine-tuning on unfiltered data, so behaviour diverges from the base model beyond refusal removal alone.
Reported scope: Not stated by the publisher. Publishers frequently omit this, so verify behaviour empirically rather than assuming full coverage.
From the publisher’s model card
“A refusal-removed GGUF build of Ornith-1.5-122B (Qwen3.5-based 122B-A10B hybrid MoE with vision). Two sizes in one repo. The vision tower (mmproj-F16.gguf) is byte-identical to the base BF16 source, so VL capability is preserved exactly.”
Running it
Commands are templates — confirm the exact repository and quant file before use.
llama.cpp / GGUF
hf download dealignai/Ornith-1.5-122B-UNCENSORED-GGUF --local-dir ./ornith-1.5-122b-uncensored
llama-cli -m ./ornith-1.5-122b-uncensored/<file>.gguf -p "..."Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer
repo = "dealignai/Ornith-1.5-122B-UNCENSORED-GGUF"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
repo, torch_dtype="auto", device_map="auto"
)vLLM
vllm serve dealignai/Ornith-1.5-122B-UNCENSORED-GGUF --trust-remote-codeDownloads and variants (4)
Every published repository of Ornith-1.5-122B-UNCENSORED, including quantised re-releases by other authors.
| Repository | Format | Downloads |
|---|---|---|
| dealignai/Ornith-1.5-122B-UNCENSORED-GGUFsource | GGUF | 27.5K |
| AtomicChat/Ornith-1.5-122B-Uncensored-GGUF | GGUF | 8.8K |
| dealignai/Ornith-1.5-122B-UNCENSORED-NVFP4 | NVFP4 | 1.5K |
| rax4901/Ornith-1.5-122B-Uncensored-GGUF | GGUF | 458 |
Security-team assessment
Derived from this model’s metadata and the publisher’s claims — not from benchmarks run by this site.
- Ornith-1.5-122B-UNCENSORED will attempt offensive-security prompts that a hosted commercial model declines, which is what makes it usable for red-team corpus generation and for measuring what an unaligned model of this class produces.
- Capability is inherited from ornith-ai/Ornith-1.5-122B, not added by ablation — at 122B parameters, expect roughly the base model’s competence, minus some instruction-following fidelity.
- The publisher does not state which layers were ablated, so assume nothing about refusal consistency — probe it directly.
- This release adds fine-tuning on unfiltered data, so its behaviour diverges from the base model beyond refusal removal — differences you measure cannot be attributed to ablation alone.
- Declared licence is mit, but the terms that bind you are ornith-ai/Ornith-1.5-122B’s — a re-release cannot grant more than its parent.
Handling: run it isolated, put moderation in front of it if anyone outside your team can reach it, and verify the weights before loading — these are third-party artifacts. Full handling and licence guidance.
Metadata for Ornith-1.5-122B-UNCENSORED is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with dealignai, and does not independently verify publisher claims. See responsible use.