Instructions to use mlx-community/SmolLM3-3B-Base-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/SmolLM3-3B-Base-4bit with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("mlx-community/SmolLM3-3B-Base-4bit") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Transformers.js
How to use mlx-community/SmolLM3-3B-Base-4bit with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-generation', 'mlx-community/SmolLM3-3B-Base-4bit'); - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use mlx-community/SmolLM3-3B-Base-4bit with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "mlx-community/SmolLM3-3B-Base-4bit" --prompt "Once upon a time"
- Xet hash:
- 376da83eeb83b6d7477346bbce2d9dbb3c0ba296a4d3a826465cc0c362874961
- Size of remote file:
- 17.2 MB
- SHA256:
- ab4da6b2aa68247e9c0fa9b97fc7fcc796505038d01f7e144522a65ce0dbd2e5
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