Model: zaakirio/LFM2.5-8B-A1B-Uncensored-GGUF Source: Original Platform
base_model, base_model_relation, quantized_by, license, license_name, license_link, library_name, pipeline_tag, language, tags
| base_model | base_model_relation | quantized_by | license | license_name | license_link | library_name | pipeline_tag | language | tags | |||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| zaakirio/LFM2.5-8B-A1B-Uncensored | quantized | zaakirio | other | lfm1.0 | https://huggingface.co/LiquidAI/LFM2.5-8B-A1B/blob/main/LICENSE | gguf | text-generation |
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LFM2.5-8B-A1B-Uncensored — GGUF
GGUF quantizations of zaakirio/LFM2.5-8B-A1B-Uncensored,
a decensored (Heretic-abliterated) version of
LiquidAI/LFM2.5-8B-A1B.
These files run with llama.cpp and any tool built on it e.g. Ollama, LM Studio, textgen, etc.
Requires a recent llama.cpp build with LFM2 MoE support. This model uses the
lfm2moearchitecture (hybrid short-conv + attention with 32 experts, 4 active per token). Only llama.cpp builds that includeLfm2MoeForCausalLMsupport can load these files. Use a current release (or current Ollama / LM Studio). Older builds will fail with an "unknown architecture 'lfm2moe'" error.
Files
| File | Quant | Size | BPW | Notes |
|---|---|---|---|---|
LFM2.5-8B-A1B-Uncensored-Q2_K.gguf |
Q2_K | 3.0 GB | 3.01 | Smallest; significant quality loss but works on very constrained hardware. |
LFM2.5-8B-A1B-Uncensored-Q3_K_S.gguf |
Q3_K_S | 3.5 GB | 3.54 | Small, lower quality. |
LFM2.5-8B-A1B-Uncensored-Q3_K_M.gguf |
Q3_K_M | 3.9 GB | 3.87 | Small; some quality loss. |
LFM2.5-8B-A1B-Uncensored-IQ4_XS.gguf |
IQ4_XS | 4.3 GB | 4.25 | Smaller than Q4_K_S with comparable quality; uses iquant scheme. |
LFM2.5-8B-A1B-Uncensored-Q4_K_S.gguf |
Q4_K_S | 4.6 GB | 4.59 | Slightly smaller than Q4_K_M. |
LFM2.5-8B-A1B-Uncensored-Q4_K_M.gguf |
Q4_K_M | 4.9 GB | 4.85 | Recommended — best size/quality balance for most users. |
LFM2.5-8B-A1B-Uncensored-Q5_K_S.gguf |
Q5_K_S | 5.5 GB | 5.49 | Higher quality. |
LFM2.5-8B-A1B-Uncensored-Q5_K_M.gguf |
Q5_K_M | 5.7 GB | 5.69 | Higher quality, marginally larger. |
LFM2.5-8B-A1B-Uncensored-Q6_K.gguf |
Q6_K | 6.5 GB | 6.56 | Near-lossless. |
LFM2.5-8B-A1B-Uncensored-Q8_0.gguf |
Q8_0 | 8.4 GB | 8.50 | Effectively lossless vs the BF16 source. |
LFM2.5-8B-A1B-Uncensored-BF16.gguf |
BF16 | 16 GB | 16.00 | Full precision, identical numerics to the source HF model. |
Not sure which to pick? Start with Q4_K_M. Go up to Q5/Q6/Q8 if you have the memory and want maximum fidelity; drop to Q3 or Q2 only if you're memory-constrained. Because this is an MoE with only ~1B active parameters per token, inference throughput is fast even at the larger quants if your hardware has the RAM.
Usage
llama.cpp (auto-download from this repo)
# Interactive chat — downloads the chosen quant automatically
llama-cli -hf zaakirio/LFM2.5-8B-A1B-Uncensored-GGUF:Q4_K_M
# OpenAI-compatible server
llama-server -hf zaakirio/LFM2.5-8B-A1B-Uncensored-GGUF:Q4_K_M -c 4096
Or, with a file you've already downloaded:
llama-cli -m LFM2.5-8B-A1B-Uncensored-Q4_K_M.gguf -p "Hello, who are you?"
Ollama
ollama run hf.co/zaakirio/LFM2.5-8B-A1B-Uncensored-GGUF:Q4_K_M
LM Studio / Jan
Search for zaakirio/LFM2.5-8B-A1B-Uncensored-GGUF in the in-app model browser,
or download a .gguf file from this page and load it.
Download a single file
pip install -U "huggingface_hub[cli]"
hf download zaakirio/LFM2.5-8B-A1B-Uncensored-GGUF \
--include "LFM2.5-8B-A1B-Uncensored-Q4_K_M.gguf" --local-dir ./
Prompt format
The chat template is embedded in the GGUF files, so chat-aware tools apply it automatically. For reference, it is ChatML-style:
<|startoftext|><|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
About the base model
This is a decensored derivative produced with Heretic
(automatic directional ablation). Compared with the original LFM2.5-8B-A1B:
| Metric | Decensored | Original |
|---|---|---|
| Refusals (/100 harmful prompts) | 0 | 0 |
| KL divergence (harmless prompts) | 0.0481 | 0 (by definition) |
The base LFM2.5-8B-A1B measured 0–2 / 100 refusals on Heretic's marker-based
detector (compared to ~98 / 100 for its smaller sibling), suggesting it is
comparatively compliant out of the box. The abliteration still makes real,
measurable changes to the attention and dense MLP projections (KL ≈ 0.05).
See the source model card for the full abliteration parameters and run details.
Intended use & disclaimer
This model has had its refusal behavior substantially removed and will comply with requests the original model would have declined. It is provided for research and unrestricted local use. You are responsible for how you use it and for complying with all applicable laws and with the base model's lfm1.0 license, which carries over to this derivative.
Provenance
- Quantized from
zaakirio/LFM2.5-8B-A1B-Uncensored(BF16) using llama.cppconvert_hf_to_gguf.py+llama-quantize. - Base model: LiquidAI/LFM2.5-8B-A1B
- Decensoring tool: Heretic by p-e-w