Instructions to use frost-beta/Llama3-33.5M-Japanese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use frost-beta/Llama3-33.5M-Japanese 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("frost-beta/Llama3-33.5M-Japanese") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use frost-beta/Llama3-33.5M-Japanese with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "frost-beta/Llama3-33.5M-Japanese" --prompt "Once upon a time"
A very tiny 33.5M Llama3 model trained on a Macbook Pro with M3 Max for 10 hours.
Complete training code can be found at https://github.com/frost-beta/train-japanese-llama3-js.
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