Text Generation
MLX
Safetensors
English
base-model
pretrained
small-language-model
apple-silicon
from-scratch
research
Instructions to use wzebrowski/OpenSML-Base-175M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use wzebrowski/OpenSML-Base-175M 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("wzebrowski/OpenSML-Base-175M") 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 wzebrowski/OpenSML-Base-175M with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "wzebrowski/OpenSML-Base-175M" --prompt "Once upon a time"
- Atomic Chat
Download SOURCE_FILES.json from wzebrowski/OpenSML-Base-175M: direct link, hf CLI and curl.
- Browser
- Download file 1.75 kB
-
https://huggingface.co/wzebrowski/OpenSML-Base-175M/resolve/main/SOURCE_FILES.json
- Command line
-
hf download hf://wzebrowski/OpenSML-Base-175M/SOURCE_FILES.json
-
curl -L -o SOURCE_FILES.json https://huggingface.co/wzebrowski/OpenSML-Base-175M/resolve/main/SOURCE_FILES.json
1.75 kB
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