Text Generation
MLX
Safetensors
English
information-extraction
structured-output
json
small-language-model
apple-silicon
from-scratch
post-training
research
Instructions to use wzebrowski/OpenSML-JSONLite-175M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use wzebrowski/OpenSML-JSONLite-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-JSONLite-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-JSONLite-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-JSONLite-175M" --prompt "Once upon a time"
- Atomic Chat
File size: 1,048 Bytes
f8ffffe 319dca0 f8ffffe 96ec8c0 f8ffffe 96ec8c0 319dca0 7a4a2b0 f8ffffe | 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 35 36 37 | {
"model_name": "OpenSML-JSONLite-175M",
"parameters": 175611648,
"model": {
"attention_impl": "fast",
"bias": false,
"ce_impl": "metal",
"d_model": 768,
"ffn_impl": "packed-metal",
"loss_dtype": "float32",
"max_seq_len": 2048,
"mlp_multiple_of": 256,
"mlp_ratio": 4.0,
"n_heads": 12,
"n_kv_heads": 4,
"n_layers": 24,
"qk_norm": true,
"rope_base": 10000.0,
"vocab_size": 32000
},
"weight_sha256": "25b406a7b86e3e8ac4dd0b7f32e27590d9d11349a0148a7815c32304150ac725",
"serialization": "native-sft-chat-v1",
"output_mode": "native-json",
"context_limit": 2048,
"weight_format": "BF16 safetensors",
"supported_runtime": "native MLX; not a Transformers or mlx-lm auto-loading export",
"max_output_tokens": 256,
"model_calls_per_request": 1,
"json_assembly": false,
"output_repair": false,
"constrained_decoding": false,
"selected_stage": "joint foundation JSON SFT",
"selected_update": 500,
"checkpoint_name": "main",
"inference_teacher_required": false
}
|