Qwythos-9B-v2
9BOtheruncensored
from empero-ai/Qwythos-9B-v2
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Dolphin3-Cyber-8B
Dolphin3-Cyber-8B is a abliterated and uncensored variant of huihui-ai/Dolphin3.0-Llama3.1-8B-abliterated, published on Hugging Face by RavichandranJ. It is 8B parameters, single consumer GPU class and llama3.1 licence. It is distributed across 5 repositories in GGUF format, totalling 50.6K downloads.
Specification
- Model name
- Dolphin3-Cyber-8B
- Source repository
- RavichandranJ/Dolphin3-Cyber-8B-GGUF
- Publisher
- RavichandranJ
- Parameters
- 8B
- Hardware class
- 4B – 10B — single consumer GPU
- Licence
- llama3.1
- Task
- Text generation
- Context window
- Not documented
- Ablation scope
- Not stated by the publisher
- Formats available
- GGUF
- First indexed
- 13 Feb 2026
- Last updated
- 21 Aug 2026
Ablation technique
How Dolphin3-Cyber-8B 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
“Dolphin3-Cyber-8B is a domain-specific large language model fine-tuned exclusively for cybersecurity applications. Built on top of the powerful Dolphin3.0-Llama3.1-8B-abliterated base model, this model has been enhanced with specialized security knowledge to serve as an AI-powered cybersecurity assistant.”
Running it
Commands are templates — confirm the exact repository and quant file before use.
Ollama (publisher-documented)
ollama run hf.co/RavichandranJ/Dolphin3-Cyber-8B-GGUF:Q4_K_Mllama.cpp / GGUF
hf download RavichandranJ/Dolphin3-Cyber-8B-GGUF --local-dir ./dolphin3-cyber-8b
llama-cli -m ./dolphin3-cyber-8b/<file>.gguf -p "..."Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer
repo = "RavichandranJ/Dolphin3-Cyber-8B-GGUF"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
repo, torch_dtype="auto", device_map="auto"
)vLLM
vllm serve RavichandranJ/Dolphin3-Cyber-8B-GGUF --trust-remote-codeDownloads and variants (4)
Every published repository of Dolphin3-Cyber-8B, including quantised re-releases by other authors.
| Repository | Format | Downloads |
|---|---|---|
| RavichandranJ/Dolphin3-Cyber-8B-GGUFsource | GGUF | 46K |
| nbpedro315/Dolphin3-Cyber-8B-GGUF | GGUF | 3.3K |
| kepom/Dolphin3-Cyber-8B-GGUF | GGUF | 775 |
| V12nm/Dolphin3-Cyber-8B-GGUF | GGUF | 562 |
Security-team assessment
Derived from this model’s metadata and the publisher’s claims — not from benchmarks run by this site.
- Dolphin3-Cyber-8B 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 huihui-ai/Dolphin3.0-Llama3.1-8B-abliterated, not added by ablation — at 8B parameters, expect a small model’s reasoning and a high error rate on exploit detail.
- 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 llama3.1, but the terms that bind you are huihui-ai/Dolphin3.0-Llama3.1-8B-abliterated’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 Dolphin3-Cyber-8B is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with RavichandranJ, and does not independently verify publisher claims. See responsible use.