Text Generation
MLX
Safetensors
English
information-extraction
structured-output
json
small-language-model
apple-silicon
from-scratch
post-training
research
Instructions to use OpenSML/OpenSML-JSONLite-175M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use OpenSML/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("OpenSML/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 OpenSML/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 "OpenSML/OpenSML-JSONLite-175M" --prompt "Once upon a time"
- Atomic Chat
Download JSONLITE_RESULTS.json from OpenSML/OpenSML-JSONLite-175M: direct link, hf CLI and curl.
- Browser
- Download file 106 kB
-
https://huggingface.co/OpenSML/OpenSML-JSONLite-175M/resolve/56c4fe441a5cd7f3ffaee7d1dc31de15cf299f0d/JSONLITE_RESULTS.json
- Command line
-
hf download hf://OpenSML/OpenSML-JSONLite-175M@56c4fe441a5cd7f3ffaee7d1dc31de15cf299f0d/JSONLITE_RESULTS.json
-
curl -L -o JSONLITE_RESULTS.json https://huggingface.co/OpenSML/OpenSML-JSONLite-175M/resolve/56c4fe441a5cd7f3ffaee7d1dc31de15cf299f0d/JSONLITE_RESULTS.json
106 kB
| { | |
| "model": "OpenSML-JSONLite-175M-Instruct", | |
| "checkpoint": "main", | |
| "selected_stage": "joint JSON extraction SFT", | |
| "step": 300, | |
| "model_sha256": "781597baeb9b51d535fc27cd6f941dbc202e01d62c8d963587a3f3d565128560", | |
| "output_mode": "native-json", | |
| "development": { | |
| "metrics": { | |
| "all": { | |
| "absent_accuracy": 0.9211356466876972, | |
| "count": 240, | |
| "counts": { | |
| "absent_correct": 292, | |
| "absent_total": 317, | |
| "exact": 178, | |
| "false_abstention": 25, | |
| "field_correct": 632, | |
| "fields": 714, | |
| "fn": 65, | |
| "fp": 47, | |
| "json_parse_ok": 240, | |
| "missed_abstention": 25, | |
| "natural_stop": 240, | |
| "nonrepetitive_nonempty": 240, | |
| "predicted_values": 504, | |
| "present_correct": 340, | |
| "present_total": 397, | |
| "schema_ok": 239, | |
| "token_limited": 0, | |
| "tp": 457, | |
| "unsupported_values": 6 | |
| }, | |
| "exact": 0.7416666666666667, | |
| "f1": 0.8908382066276802, | |
| "false_abstention_rate": 0.06297229219143577, | |
| "field_accuracy": 0.8851540616246498, | |
| "json_parse_rate": 1.0, | |
| "missed_abstention_rate": 0.07886435331230283, | |
| "natural_stop_rate": 1.0, | |
| "nonrepetitive_nonempty_rate": 1.0, | |
| "output_nll": 0.04828121321412861, | |
| "precision": 0.9067460317460317, | |
| "present_accuracy": 0.8564231738035264, | |
| "recall": 0.8754789272030651, | |
| "schema_valid_rate": 0.9958333333333333, | |
| "token_limited_rate": 0.0, | |
| "unsupported_value_rate": 0.011904761904761904 | |
| }, | |
| "domain/AddToPlaylist": { | |
| "absent_accuracy": 0.8974358974358975, | |
| "count": 28, | |
| "counts": { | |
| "absent_correct": 35, | |
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| "exact": 19, | |
| "false_abstention": 1, | |
| "field_correct": 81, | |
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| "fp": 10, | |
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| }, | |
| "domain/BookRestaurant": { | |
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| "domain/GetWeather": { | |
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| }, | |
| "domain/roles": { | |
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