Instructions to use FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6-GGUF",
	filename="LFM2.5-1.2B-Distilled-Claude-4.6-F16.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6-GGUF:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6-GGUF:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6-GGUF:Q4_K_M

Use Docker

docker model run hf.co/FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6-GGUF with Ollama:
```
ollama run hf.co/FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6-GGUF:Q4_K_M
```

Unsloth Studio

How to use FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6-GGUF to start chatting

Docker Model Runner
How to use FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6-GGUF with Docker Model Runner:
```
docker model run hf.co/FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6-GGUF:Q4_K_M
```

Lemonade

How to use FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.LFM2.5-1.2B-Distilled-Claude-4.6-GGUF-Q4_K_M

List all available models

lemonade list

LFM2.5-1.2B-Distilled-Claude-4.6 (Liquid Claude)

LFM2.5-1.2B-Distilled-Claude-4.6 (Liquid Claude) is a distillation of Claude into LFM2.5-1.2B-Thinking via LoRA.

Training data info:

THINK BLOCK PATTERNS
Agentic think blocks (Action/Observation): 8473
Pure reasoning think blocks: 3005

CONSECUTIVE USER MESSAGES
Total consecutive user-user pairs: 319

MESSAGE LENGTH STATS (chars)

:)	msgs	avg	max
System	2325	2168	2168
User	11919	332	39134
Assistant	11738	4386	264340

Assistant messages total: 11738
With agentic tool calls in think: 2151 (18.3%)

Total chars in dataset: 60,487,999
Approx tokens (~4 chars/token): 15,121,999

Conversations with <=2 messages (system+1): 121
Conversations with >5 think blocks in a single assistant msg: 319

Sample chat:

(Ignore the fact that it took 1min to reason, i got a i3-6006u / 12GB as hardware and running the f16 quantization)

Benchmark

The results are in progress.

Downloads last month: 684

GGUF

Model size

1B params

Architecture

lfm2

Hardware compatibility

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

16-bit

Inference Providers NEW

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Model tree for FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6-GGUF

Base model

LiquidAI/LFM2.5-1.2B-Base

Finetuned

LiquidAI/LFM2.5-1.2B-Thinking

Finetuned

FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6

Quantized

(3)

this model

Collection including FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6-GGUF

Liquid Claude

Collection

Liquid Claude is a small series of LiquidAI/LFM2.5-1.2B-Thinking model that have been fine tuned on Claude chats/data. • 6 items • Updated 12 days ago • 2