Llama3.3-8B-Instruct-Thinking-Heretic-Uncensored-Claude-4.5-Opus-High-Reasoning
8BLlamaheretic
from allura-forge/Llama-3.3-8B-Instruct
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Llama-Poro-2-8B-Long-Instruct-heretic
Llama-Poro-2-8B-Long-Instruct-heretic is a Heretic-ablated variant of dufuspaelli/Llama-Poro-2-8B-Long-Instruct-heretic, published on Hugging Face by dufuspaelli. It is 8B parameters, single consumer GPU class and llama3.3 licence. It is distributed across 5 repositories in Transformers, GGUF and GGUF (imatrix) formats, totalling 5.5K downloads.
Specification
- Model name
- Llama-Poro-2-8B-Long-Instruct-heretic
- Source repository
- dufuspaelli/Llama-Poro-2-8B-Long-Instruct-heretic
- Publisher
- dufuspaelli
- Parameters
- 8B
- Hardware class
- 4B – 10B — single consumer GPU
- Licence
- llama3.3
- Task
- Text generation
- Context window
- Not documented
- Ablation scope
- Not stated by the publisher
- Formats available
- Transformers, GGUF, GGUF (imatrix)
- First indexed
- 26 Aug 2026
- Last updated
- 27 Aug 2026
Ablation technique
How Llama-Poro-2-8B-Long-Instruct-heretic was modified, and what that implies.
Heretic
Automated directional ablation via the Heretic toolchain, which searches for the refusal direction and applies it with a KL-divergence budget so general capability is preserved.
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
“Poro 2 Long Instruct is an instruction-following chatbot model with extended context support, created through supervised fine-tuning (SFT) of the Poro 2 Long Base model followed by merging the SFT checkpoint back with the base model to preserve long-context performance. This model is designed for conversational AI...”
Running it
Commands are templates — confirm the exact repository and quant file before use.
llama.cpp / GGUF
hf download mradermacher/Llama-Poro-2-8B-Long-Instruct-heretic-i1-GGUF --local-dir ./llama-poro-2-8b-long-instruct-heretic
llama-cli -m ./llama-poro-2-8b-long-instruct-heretic/<file>.gguf -p "..."Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer
repo = "dufuspaelli/Llama-Poro-2-8B-Long-Instruct-heretic"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
repo, torch_dtype="auto", device_map="auto"
)vLLM
vllm serve dufuspaelli/Llama-Poro-2-8B-Long-Instruct-heretic --trust-remote-codeDownloads and variants (4)
Every published repository of Llama-Poro-2-8B-Long-Instruct-heretic, including quantised re-releases by other authors.
| Repository | Format | Downloads |
|---|---|---|
| mradermacher/Llama-Poro-2-8B-Long-Instruct-heretic-i1-GGUF | GGUF (imatrix) | 4.4K |
| mradermacher/Llama-Poro-2-8B-Long-Instruct-heretic-GGUF | GGUF | 690 |
| dufuspaelli/Llama-Poro-2-8B-Long-Instruct-hereticsource | Transformers | 266 |
| dufuspaelli/Llama-Poro-2-8B-Long-Instruct-heretic-Q4_K_M-GGUF | GGUF | 101 |
Security-team assessment
Derived from this model’s metadata and the publisher’s claims — not from benchmarks run by this site.
- Llama-Poro-2-8B-Long-Instruct-heretic 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 dufuspaelli/Llama-Poro-2-8B-Long-Instruct-heretic, 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.
- Declared licence is llama3.3, but the terms that bind you are dufuspaelli/Llama-Poro-2-8B-Long-Instruct-heretic’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 Llama-Poro-2-8B-Long-Instruct-heretic is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with dufuspaelli, and does not independently verify publisher claims. See responsible use.