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
File size: 1,240 Bytes
7708682 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | {
"name": "sml-v2-150m-pilot-v1",
"data_mode": "hf_stream",
"stream": {"prefetch_batches": 4, "read_attempts": 5, "dedup_window": 10000},
"model": {"vocab_size": 32000, "max_seq_len": 2048, "d_model": 768, "n_layers": 20, "n_heads": 12, "n_kv_heads": 4, "mlp_ratio": 4.0, "mlp_multiple_of": 256, "bias": false, "qk_norm": true, "attention_impl": "fast", "loss_dtype": "float32", "ce_impl": "metal", "ffn_impl": "packed-metal"},
"seed": 7337,
"batches": [4, 3, 3, 3],
"grad_accum": 4,
"target_tokens": 500000000,
"peak_lr": 0.0003,
"warmup_fraction": 0.01,
"decay_start_fraction": 0.8,
"min_lr_ratio": 0.1,
"betas": [0.9, 0.95],
"eps": 1e-8,
"weight_decay": 0.1,
"grad_clip": 1.0,
"eval_every_tokens": 25000000,
"sample_every_tokens": 50000000,
"save_every_tokens": 10000000,
"eval_batches_per_source": 16,
"eval_batch_size": 2,
"keep_checkpoints": 2,
"reserve_gib": 8,
"log_every": 10,
"prompts": [
"The library was closed for repairs, so Maya decided to",
"Plants need sunlight because",
"A useful way to remember a new word is to",
"The train arrived late because of heavy snow. When the passengers stepped outside,",
"Clean drinking water is important because"
]
}
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