base_model: ops-malware/smollm2-1.7b-abliterated base_model_relation: quantized library_name: gguf pipeline_tag: text-generation language:
- en license: apache-2.0 tags:
- gguf
- llama.cpp
- abliterated
- uncensored
- senbonzakura
smollm2-1.7b-abliterated-GGUF
Correction notice, 2026-10-01
The evaluation numbers for this model are withdrawn. They were never printed on this card; they live on the parent repository's card, and every one of them is withdrawn there, with the reasons. The GGUF files themselves are unchanged and are not withdrawn.
Read the notice on smollm2-1.7b-abliterated before quoting any figure for this model.
GGUF builds of ops-malware/smollm2-1.7b-abliterated, for llama.cpp, Ollama, LM Studio and Jan.
The parent card carries what this model is, how it was made, what abliteration did to it, and the evaluation numbers. Read it before using these weights: this model does not refuse, which is the entire point of it and the thing to understand before downloading.
Files
| File | Precision | Size | Use when |
|---|---|---|---|
smollm2-1.7b-f16.gguf | F16 | larger | You want the conversion with no quantisation loss, or you are making your own quants |
smollm2-1.7b-Q4_K_M.gguf | Q4_K_M | ~4x smaller | Almost always. The usual quality and size compromise |
Both were converted from the parent's safetensors with convert_hf_to_gguf.py
and quantised with llama-quantize. Each file was loaded and asked to generate
before publication, because a GGUF that converts but does not run is exactly the
kind of thing that ships broken.
Usage
llama.cpp
llama-server -m smollm2-1.7b-Q4_K_M.gguf -c 4096
Ollama
ollama run hf.co/ops-malware/smollm2-1.7b-abliterated-GGUF:Q4_K_M
Python, via huggingface_hub
from huggingface_hub import hf_hub_download
path = hf_hub_download(
repo_id="ops-malware/smollm2-1.7b-abliterated-GGUF",
filename="smollm2-1.7b-Q4_K_M.gguf",
)
Limitations
Everything on the parent card applies here unchanged, plus the usual quantisation caveat: Q4_K_M trades some quality for size, and small models have less quality to spare than large ones. If a result matters, check it against the F16.