Image-Text-to-Text
MLX
Safetensors
gemma4
lemma
8bit
apple-silicon
multimodal
on-device
conversational
Instructions to use lthn/lemma-mlx-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use lthn/lemma-mlx-8bit with MLX:
# Make sure mlx-vlm is installed # pip install --upgrade mlx-vlm from mlx_vlm import load, generate from mlx_vlm.prompt_utils import apply_chat_template from mlx_vlm.utils import load_config # Load the model model, processor = load("lthn/lemma-mlx-8bit") config = load_config("lthn/lemma-mlx-8bit") # Prepare input image = ["http://images.cocodataset.org/val2017/000000039769.jpg"] prompt = "Describe this image." # Apply chat template formatted_prompt = apply_chat_template( processor, config, prompt, num_images=1 ) # Generate output output = generate(model, processor, formatted_prompt, image) print(output) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Pi
How to use lthn/lemma-mlx-8bit with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "lthn/lemma-mlx-8bit"
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "lthn/lemma-mlx-8bit" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent
How to use lthn/lemma-mlx-8bit with Hermes Agent:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "lthn/lemma-mlx-8bit"
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 lthn/lemma-mlx-8bit
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use lthn/lemma-mlx-8bit with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "lthn/lemma-mlx-8bit"
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 "lthn/lemma-mlx-8bit" \ --custom-provider-id mlx-lm \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
File size: 1,389 Bytes
83cdd24 d296bbb 83cdd24 fa76a33 83cdd24 fa76a33 83cdd24 fa76a33 | 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 38 | ---
library_name: mlx
pipeline_tag: image-text-to-text
tags:
- gemma4
- lemma
- mlx
- 8bit
- apple-silicon
- multimodal
- on-device
- conversational
license: eupl-1.2
license_link: https://ai.google.dev/gemma/docs/gemma_4_license
base_model:
- lthn/lemma
base_model_relation: quantized
---
# Lemma — Gemma 4 E4B — MLX 8-bit
The mid-sized member of the Lemma model family by Lethean. An EUPL-1.2 fork of Gemma 4 E4B with the Lethean Ethical Kernel (LEK) merged into the weights.
This repo hosts the **MLX 8-bit** build for native Apple Silicon inference via [`mlx-lm`](https://github.com/ml-explore/mlx-lm) and [`mlx-vlm`](https://github.com/Blaizzy/mlx-vlm). For the GGUF playground (Ollama, llama.cpp) see [`lthn/lemma`](https://huggingface.co/lthn/lemma). For the unmodified Google base see [`LetheanNetwork/lemma`](https://huggingface.co/LetheanNetwork/lemma).
## Family
| Repo | Format | Bits |
|---|---|---|
| [`lthn/lemma`](https://huggingface.co/lthn/lemma) | GGUF multi-quant | Q4_K_M → BF16 |
| [`lthn/lemma-mlx`](https://huggingface.co/lthn/lemma-mlx) | MLX | 4-bit |
| [`lthn/lemma-mlx-8bit`](https://huggingface.co/lthn/lemma-mlx-8bit) | MLX | 8-bit |
| [`lthn/lemma-mlx-bf16`](https://huggingface.co/lthn/lemma-mlx-bf16) | MLX | bf16 |
## License
EUPL-1.2. See [Gemma Terms of Use](https://ai.google.dev/gemma/docs/gemma_4_license) for upstream base model terms.
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