Instructions to use HelioAI/LFM3-1.7B-inference-modules-experiments with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use HelioAI/LFM3-1.7B-inference-modules-experiments with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M
# Run inference directly in the terminal:
llama cli -hf HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M
# Run inference directly in the terminal:
llama cli -hf HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M

Build from source code

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M
# Run inference directly in the terminal:
./build/bin/llama cli -hf HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M

Use Docker

docker model run hf.co/HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M

Llama new
LM Studio
Jan
Ollama
How to use HelioAI/LFM3-1.7B-inference-modules-experiments with Ollama:
```
ollama run hf.co/HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M
```
Unsloth Desktop

How to use HelioAI/LFM3-1.7B-inference-modules-experiments with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use HelioAI/LFM3-1.7B-inference-modules-experiments with Docker Model Runner:
```
docker model run hf.co/HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M
```

Lemonade

How to use HelioAI/LFM3-1.7B-inference-modules-experiments with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M

Run and chat with the model

lemonade run user.LFM3-1.7B-inference-modules-experiments-Q5_K_M

List all available models

lemonade list

Hermes Agent

How to use HelioAI/LFM3-1.7B-inference-modules-experiments with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use HelioAI/LFM3-1.7B-inference-modules-experiments with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "HelioAI/LFM3-1.7B-inference-modules-experiments:Q5_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

LFM3-1.7B-inference-modules-experiments / research /scripts /expo.py

HelioAI

LFM3-1.7B inference modules: experimental release

67ebcef verified 3 days ago

Raw History Blame Contribute Delete

872 Bytes

"""Weight extrapolation (ExPO): theta = theta_inst + alpha * (theta_inst - theta_base)."""
import os, shutil, sys, torch
from safetensors.torch import load_file, save_file
alpha, out = float(sys.argv[1]), sys.argv[2]
inst = load_file("models/LFM3-1.7B/model.safetensors")
base = load_file("models/LFM3-1.7B-Base/model.safetensors")
new = {}
for k, v in inst.items():
    b = base.get(k)
    new[k] = v if b is None or b.shape != v.shape else (v.float() + alpha * (v.float() - b.float())).to(v.dtype)
os.makedirs(out, exist_ok=True)
save_file(new, os.path.join(out, "model.safetensors"), metadata={"format": "pt"})
for f in os.listdir("models/LFM3-1.7B"):
    if f != "model.safetensors" and os.path.isfile(os.path.join("models/LFM3-1.7B", f)):
        shutil.copy(os.path.join("models/LFM3-1.7B", f), out)
print("missing in base:", [k for k in inst if k not in base][:5])

	"""Weight extrapolation (ExPO): theta = theta_inst + alpha * (theta_inst - theta_base)."""
	import os, shutil, sys, torch
	from safetensors.torch import load_file, save_file
	alpha, out = float(sys.argv[1]), sys.argv[2]
	inst = load_file("models/LFM3-1.7B/model.safetensors")
	base = load_file("models/LFM3-1.7B-Base/model.safetensors")
	new = {}
	for k, v in inst.items():
	b = base.get(k)
	new[k] = v if b is None or b.shape != v.shape else (v.float() + alpha * (v.float() - b.float())).to(v.dtype)
	os.makedirs(out, exist_ok=True)
	save_file(new, os.path.join(out, "model.safetensors"), metadata={"format": "pt"})
	for f in os.listdir("models/LFM3-1.7B"):
	if f != "model.safetensors" and os.path.isfile(os.path.join("models/LFM3-1.7B", f)):
	shutil.copy(os.path.join("models/LFM3-1.7B", f), out)
	print("missing in base:", [k for k in inst if k not in base][:5])