---
license: other
license_name: lfm-1.0
license_link: https://huggingface.co/LiquidAI/LFM2.5-1.2B-Thinking/blob/main/LICENSE
language:
- en
- ar
- zh
- fr
- de
- ja
- ko
- es
pipeline_tag: text-generation
tags:
- gguf
- llama.cpp
- quantized
- q8_0
- liquid-ai
- lfm
- lfm2
- conversational
base_model: LiquidAI/LFM2.5-1.2B-Thinking
---

# LFM 2.5 1.2B Thinking (GGUF)

## Description

This repository contains the **GGUF** quantized version of [LiquidAI/LFM2.5-1.2B-Thinking](https://huggingface.co/LiquidAI/LFM2.5-1.2B-Thinking), a 1.2 billion parameter "thinking" language model by **Liquid AI**.

The model uses the novel `Lfm2ForCausalLM` architecture featuring a hybrid design of **10 double-gated LIV convolution blocks + 6 GQA attention blocks** — a departure from standard transformer-only designs. This architecture alternates between local convolution-based mixing and sparse global attention, enabling efficient sequence processing with strong reasoning capabilities.

## Model Details

| Property | Value |
|---|---|
| **Architecture** | Lfm2ForCausalLM |
| **Parameter Count** | 1.17B |
| **Layers** | 16 (10 conv blocks + 6 GQA blocks) |
| **Hidden Size** | 2048 |
| **Intermediate (FFN)** | 8192 |
| **Attention Heads** | 32 |
| **KV Heads (GQA)** | 8 (on attention layers) |
| **Context Length** | 32,768 tokens |
| **Vocabulary Size** | 65,536 |
| **Languages** | English, Arabic, Chinese, French, German, Japanese, Korean, Spanish |
| **Quantization** | Q8_0 (8-bit) |
| **File Type** | GGUF |

## Quantization Details

This model was quantized using **llama.cpp** with the `Q8_0` scheme:

- **Source format**: F16 (converted from HuggingFace safetensors)
- **Quantization**: Q8_0 — 8-bit quantization with block-wise scaling
- **Quality**: Near-lossless; ideal for deployment where precision matters
- **Size reduction**: ~50% smaller than F16 while retaining virtually all model quality

## Usage with llama.cpp
```bash
git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build && cmake --build build --config Release -j$(nproc)

./build/bin/llama-cli \
  -hf Kelexine/LFM2.5-1.2B-Thinking-GGUF \
  --temp 0.05 --top-k 50 --repeat-penalty 1.05 -n 4096 -cnv
```

Or with a local file:
```bash
./build/bin/llama-cli \
  -m LFM2.5-1.2B-Thinking-Q8_0.gguf \
  -p "<|im_start|>user\nYour prompt here<|im_end|>\n<|im_start|>assistant\n" \
  --temp 0.05 --top-k 50 --repeat-penalty 1.05 -n 4096
```

## Usage with Python (llama-cpp-python)
```python
from llama_cpp import Llama

llm = Llama(
    model_path="LFM2.5-1.2B-Thinking-Q8_0.gguf",
    n_ctx=4096,
    temperature=0.05,
    top_k=50,
    repeat_penalty=1.05,
)

response = llm(
    "<|im_start|>user\nWhat is machine learning?<|im_end|>\n<|im_start|>assistant\n",
    max_tokens=4096,
    stop=["<|im_end|>"],
)
print(response["choices"][0]["text"])
```

## Provided Files

| File | Description |
|---|---|
| `LFM2.5-1.2B-Thinking-Q8_0.gguf` | 8-bit quantized GGUF (recommended) |

## Limitations

- This is a 1.17B parameter model — suited for lightweight tasks, quick prototyping, and edge deployment.
- The "Thinking" variant is designed for chain-of-thought reasoning but may produce verbose `<think>...</think>` blocks; strip these in downstream integrations.
- Requires a recent version of llama.cpp with `Lfm2ForCausalLM` architecture support.
- Not recommended for knowledge-intensive tasks or programming per Liquid AI's own guidance.

## License

This repository inherits the [LFM 1.0 License](https://huggingface.co/LiquidAI/LFM2.5-1.2B-Thinking/blob/main/LICENSE) from the base model [LiquidAI/LFM2.5-1.2B-Thinking](https://huggingface.co/LiquidAI/LFM2.5-1.2B-Thinking).

## Credits

- **Base model**: [Liquid AI](https://www.liquid.ai/)
- **Quantization**: kelexine
- **Framework**: [llama.cpp](https://github.com/ggml-org/llama.cpp) by ggml-org