Text Generation
MLX
English
sol_lassi
causal-lm
decoder-only
small-language-model
experimental
sol-intelligence
Instructions to use solintellegence/Sol-Lassi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use solintellegence/Sol-Lassi 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("solintellegence/Sol-Lassi") 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 solintellegence/Sol-Lassi with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "solintellegence/Sol-Lassi" --prompt "Once upon a time"
- Atomic Chat
Download keystone_mlx/__init__.py from solintellegence/Sol-Lassi: direct link, hf CLI and curl.
- Browser
- Download file 205 Bytes
-
https://huggingface.co/solintellegence/Sol-Lassi/resolve/main/keystone_mlx/__init__.py
- Command line
-
hf download hf://solintellegence/Sol-Lassi/keystone_mlx/__init__.py
-
curl -L -o __init__.py https://huggingface.co/solintellegence/Sol-Lassi/resolve/main/keystone_mlx/__init__.py
205 Bytes
| """Metal/MLX training implementation for the experimental Keystone-2M model.""" | |
| from .model import DEFAULT_CONFIG, KeystoneConfig, KeystoneLM | |
| __all__ = ["DEFAULT_CONFIG", "KeystoneConfig", "KeystoneLM"] | |