Text Generation
MLX
Safetensors
English
pretraining
from-scratch
small-language-model
post-training
silicon
Instructions to use OpenSML/OpenSML-150M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use OpenSML/OpenSML-150M 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("OpenSML/OpenSML-150M") 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 OpenSML/OpenSML-150M with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "OpenSML/OpenSML-150M" --prompt "Once upon a time"
- Atomic Chat
Download corpus.json from OpenSML/OpenSML-150M: direct link, hf CLI and curl.
- Browser
- Download file 1.55 kB
-
https://huggingface.co/OpenSML/OpenSML-150M/resolve/main/corpus.json
- Command line
-
hf download hf://OpenSML/OpenSML-150M/corpus.json
-
curl -L -o corpus.json https://huggingface.co/OpenSML/OpenSML-150M/resolve/main/corpus.json
1.55 kB
| { | |
| "max_bytes": 200000, | |
| "max_rows_per_source": 5000000, | |
| "min_chars": 200, | |
| "name": "sml-v2-educational-prose-v1", | |
| "seed": 7337, | |
| "shuffle_buffer": 10000, | |
| "sources": [ | |
| { | |
| "config": "fineweb-edu-dedup", | |
| "label": "web", | |
| "license": "ODC-BY; preserve underlying source notices", | |
| "repo": "HuggingFaceTB/smollm-corpus", | |
| "revision": "3ba9d605774198c5868892d7a8deda78031a781f", | |
| "split": "train", | |
| "text_field": "text", | |
| "weight": 55 | |
| }, | |
| { | |
| "label": "dclm", | |
| "license": "CC-BY-4.0", | |
| "min_score": { | |
| "field": "edu_int_score", | |
| "value": 3 | |
| }, | |
| "repo": "HuggingFaceTB/dclm-edu", | |
| "revision": "dbad8ad71224482740cd9c9d353591adbf62fe04", | |
| "split": "train", | |
| "text_field": "text", | |
| "weight": 25 | |
| }, | |
| { | |
| "config": "en", | |
| "label": "wiki", | |
| "license": "CC-BY-SA-4.0 / GFDL", | |
| "repo": "HuggingFaceFW/finewiki", | |
| "revision": "8bd13e72e6a002407649b3e898535f42ceb1aeb9", | |
| "split": "train", | |
| "text_field": "text", | |
| "weight": 10 | |
| }, | |
| { | |
| "config": "cosmopedia-v2", | |
| "format_contains": [ | |
| "textbook", | |
| "tutorial", | |
| "blog", | |
| "educational" | |
| ], | |
| "label": "cosmopedia", | |
| "license": "ODC-BY; synthetic content; preserve provenance", | |
| "repo": "HuggingFaceTB/smollm-corpus", | |
| "revision": "3ba9d605774198c5868892d7a8deda78031a781f", | |
| "split": "train", | |
| "text_field": "text", | |
| "weight": 10 | |
| } | |
| ], | |
| "split_buckets": 10000 | |
| } | |