Text Generation
GGUF
English
dictation
voice
speech-postprocessing
text-cleanup
lfm2
llama-cpp
on-device
conversational
Instructions to use PromethicLabs/Emberon-1.2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use PromethicLabs/Emberon-1.2B with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="PromethicLabs/Emberon-1.2B", filename="Emberon-1.2B-F16.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use PromethicLabs/Emberon-1.2B 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 PromethicLabs/Emberon-1.2B:F16 # Run inference directly in the terminal: llama cli -hf PromethicLabs/Emberon-1.2B:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf PromethicLabs/Emberon-1.2B:F16 # Run inference directly in the terminal: llama cli -hf PromethicLabs/Emberon-1.2B:F16
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 PromethicLabs/Emberon-1.2B:F16 # Run inference directly in the terminal: ./llama-cli -hf PromethicLabs/Emberon-1.2B:F16
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 PromethicLabs/Emberon-1.2B:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf PromethicLabs/Emberon-1.2B:F16
Use Docker
docker model run hf.co/PromethicLabs/Emberon-1.2B:F16
- LM Studio
- Jan
- vLLM
How to use PromethicLabs/Emberon-1.2B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "PromethicLabs/Emberon-1.2B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "PromethicLabs/Emberon-1.2B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/PromethicLabs/Emberon-1.2B:F16
- Ollama
How to use PromethicLabs/Emberon-1.2B with Ollama:
ollama run hf.co/PromethicLabs/Emberon-1.2B:F16
- Unsloth Studio
How to use PromethicLabs/Emberon-1.2B 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 PromethicLabs/Emberon-1.2B 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 PromethicLabs/Emberon-1.2B to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for PromethicLabs/Emberon-1.2B to start chatting
- Pi
How to use PromethicLabs/Emberon-1.2B with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf PromethicLabs/Emberon-1.2B:F16
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "PromethicLabs/Emberon-1.2B:F16" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use PromethicLabs/Emberon-1.2B with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf PromethicLabs/Emberon-1.2B:F16
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 PromethicLabs/Emberon-1.2B:F16
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use PromethicLabs/Emberon-1.2B with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf PromethicLabs/Emberon-1.2B:F16
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 "PromethicLabs/Emberon-1.2B:F16" \ --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"
- Docker Model Runner
How to use PromethicLabs/Emberon-1.2B with Docker Model Runner:
docker model run hf.co/PromethicLabs/Emberon-1.2B:F16
- Lemonade
How to use PromethicLabs/Emberon-1.2B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull PromethicLabs/Emberon-1.2B:F16
Run and chat with the model
lemonade run user.Emberon-1.2B-F16
List all available models
lemonade list
File size: 1,659 Bytes
724ccad 71625cf 724ccad | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 | Emberon-1.2B
============
Emberon-1.2B is a fine-tune (LoRA, fused) of:
LiquidAI/LFM2.5-1.2B-Instruct
Copyright © Liquid AI
Licensed under the LFM Open License v1.0 — https://www.liquid.ai/lfm-license
This product includes a MODIFIED version of LFM2.5-1.2B-Instruct. The model weights were
adapted by Promethic Labs to perform dictation cleanup (rewriting raw voice transcripts into
clean text without answering or executing them). The base architecture and pretrained weights
are the work of Liquid AI; the modification is the work of Promethic Labs.
Modifications © 2026 Promethic Labs (https://wispercode.com)
In accordance with Section 4 of the LFM Open License v1.0:
- a copy of the License is included (see LICENSE);
- the original attribution/copyright notices are retained (above);
- this NOTICE states that the files were changed from the original.
ATTRIBUTION
-----------
REQUIRED (redistribution & derivatives): If you redistribute these weights, or release a
fine-tune, merge, quantization, or other derivative of Emberon, you must retain this NOTICE
and the copyright notices above (BOTH Liquid AI and Promethic Labs), state that you modified
the model, and include the LICENSE.
REQUESTED (use in products, services, or research): Please credit Promethic Labs. Suggested
credit line:
Powered by Emberon-1.2B by Promethic Labs (https://promethic.xyz) — a dictation-cleanup
fine-tune of LiquidAI/LFM2.5-1.2B-Instruct.
Trademarks: "Liquid AI" and "LFM" are trademarks of Liquid AI. "Promethic Labs", "Emberon",
and "WisperCode" are trademarks of Promethic Labs. Use of a name does not imply endorsement.
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