⌦abliteratedmodels.org

Agents-A1-Uncensored

Agents-A1-Uncensored is a abliterated and uncensored variant of InternScience/Agents-A1, published on Hugging Face by SC117. It is apache-2.0 licence. It is distributed across 2 repositories in GGUF format, totalling 12.6K downloads.

Abliteration + uncensored fine-tuneOther↓ 12,632♥ 16
View on Hugging Face ↗Base model ↗

Specification

Model name
Agents-A1-Uncensored
Source repository
SC117/Agents-A1-Uncensored-MTP-APEX-GGUF
Base model
InternScience/Agents-A1
Publisher
SC117
Parameters
Not determinable from name
Hardware class
Unknown
Licence
apache-2.0
Task
Text generation
Context window
Not documented
Ablation scope
Not stated by the publisher
Formats available
GGUF
First indexed
18 Jul 2026
Last updated
21 Jul 2026

Ablation technique

How Agents-A1-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

“Uncensored 35B agentic MoE · APEX-quantized GGUFs + MTP + BF16 mmproj”

Running it

Commands are templates — confirm the exact repository and quant file before use.

llama.cpp / GGUF
hf download SC117/Agents-A1-Uncensored-MTP-APEX-GGUF --local-dir ./agents-a1-uncensored
llama-cli -m ./agents-a1-uncensored/<file>.gguf -p "..."
Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer

repo = "SC117/Agents-A1-Uncensored-MTP-APEX-GGUF"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
    repo, torch_dtype="auto", device_map="auto"
)
vLLM
vllm serve SC117/Agents-A1-Uncensored-MTP-APEX-GGUF --trust-remote-code

Downloads and variants (1)

The only published repository of Agents-A1-Uncensored.

RepositoryFormatDownloads
SC117/Agents-A1-Uncensored-MTP-APEX-GGUFsourceGGUF12.6K

Security-team assessment

Derived from this model’s metadata and the publisher’s claims — not from benchmarks run by this site.

  • Agents-A1-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.
  • 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 apache-2.0, but the terms that bind you are InternScience/Agents-A1’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 Agents-A1-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 SC117, and does not independently verify publisher claims. See responsible use.