--- base_model: zaakirio/LFM2.5-8B-A1B-Uncensored base_model_relation: quantized quantized_by: zaakirio license: other license_name: lfm1.0 license_link: https://huggingface.co/LiquidAI/LFM2.5-8B-A1B/blob/main/LICENSE library_name: gguf pipeline_tag: text-generation language: - en - ar - zh - fr - de - ja - ko - es - pt tags: - heretic - abliterated - decensored - uncensored - liquid - lfm2 - lfm2.5 - moe - edge - gguf - llama.cpp - conversational --- # LFM2.5-8B-A1B-Uncensored — GGUF GGUF quantizations of [`zaakirio/LFM2.5-8B-A1B-Uncensored`](https://huggingface.co/zaakirio/LFM2.5-8B-A1B-Uncensored), a decensored ([Heretic](https://github.com/p-e-w/heretic)-abliterated) version of [`LiquidAI/LFM2.5-8B-A1B`](https://huggingface.co/LiquidAI/LFM2.5-8B-A1B). These files run with [llama.cpp](https://github.com/ggml-org/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 `lfm2moe` architecture (hybrid short-conv + attention with 32 experts, > 4 active per token). Only llama.cpp builds that include `Lfm2MoeForCausalLM` > support 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) ```bash # 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: ```bash llama-cli -m LFM2.5-8B-A1B-Uncensored-Q4_K_M.gguf -p "Hello, who are you?" ``` ### Ollama ```bash 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 ```bash 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](https://github.com/p-e-w/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](https://huggingface.co/zaakirio/LFM2.5-8B-A1B-Uncensored) 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](https://huggingface.co/LiquidAI/LFM2.5-8B-A1B/blob/main/LICENSE), which carries over to this derivative. ## Provenance - Quantized from `zaakirio/LFM2.5-8B-A1B-Uncensored` (BF16) using llama.cpp `convert_hf_to_gguf.py` + `llama-quantize`. - Base model: [LiquidAI/LFM2.5-8B-A1B](https://huggingface.co/LiquidAI/LFM2.5-8B-A1B) - Decensoring tool: [Heretic](https://github.com/p-e-w/heretic) by p-e-w