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
Use JSONLite Instruct model name in the model card
Browse files- README.md +7 -7
- SHA256SUMS +1 -1
README.md
CHANGED
|
@@ -21,9 +21,9 @@ datasets:
|
|
| 21 |
- databricks/databricks-dolly-15k
|
| 22 |
---
|
| 23 |
|
| 24 |
-
# OpenSML-JSONLite-175M
|
| 25 |
|
| 26 |
-
**Author:** William Zebrowski · **
|
| 27 |
|
| 28 |
[Technical report](TECHNICAL_REPORT.md) · [Results](JSONLITE_RESULTS.json) · [Checkpoint provenance](checkpoint_provenance.json) · [Native inference verification](INFERENCE_VERIFICATION.json) · [Source repository](https://github.com/williamzebrowskI/OpenSML-JSONLite-175M)
|
| 29 |
|
|
@@ -86,7 +86,7 @@ The frozen byte-level BPE tokenizer was fitted for the earlier OpenSML project a
|
|
| 86 |
## Training and model lineage
|
| 87 |
|
| 88 |
```text
|
| 89 |
-
Stage A pretrained/132005 → SFT-065/469 → SFT-068/379 →
|
| 90 |
```
|
| 91 |
|
| 92 |
Only those selected stages are inherited. The many intervening research trials and failed RL/JSON experiments are not additional ancestors of the final weights.
|
|
@@ -140,7 +140,7 @@ All three SFT stages update the full model on Mac1 with assistant-output-only me
|
|
| 140 |
|
| 141 |
The inherited post-training totals are **1,008 updates**, **32,243 presentations** and **5,646,323 serialized tokens**. These counts include repeated source views, and serialized token accounting includes prompt positions masked out of the loss.
|
| 142 |
|
| 143 |
-
|
| 144 |
|
| 145 |
## Supported schema contract
|
| 146 |
|
|
@@ -189,7 +189,7 @@ The model produced separate labeled `track`, `artist` and `album` answers; the a
|
|
| 189 |
|
| 190 |
### Complete-request correctness
|
| 191 |
|
| 192 |
-
| Panel | Parent SFT-068/379, same adapter | JSONLite
|
| 193 |
| --- | --- | --- |
|
| 194 |
| Observed development | 139/196 — 70.92% | **168/196 — 85.71%** |
|
| 195 |
| Observed adapted SNIPS held-out | 953/1,388 — 68.66% | **1,132/1,388 — 81.56%** |
|
|
@@ -218,7 +218,7 @@ The model produced separate labeled `track`, `artist` and `album` answers; the a
|
|
| 218 |
|
| 219 |
The held-out panel has 694 original source texts with two different requested-field views each, across seven SNIPS categories. Whole-request exact improves in every category under the same route, while present-field recall and false abstentions regress. The parent’s older **83.50% joint-labeled** test uses a different protocol and is not this table’s fieldwise JSON baseline.
|
| 220 |
|
| 221 |
-
The
|
| 222 |
|
| 223 |
<details>
|
| 224 |
<summary>Protocol, metrics and evaluation independence</summary>
|
|
@@ -243,7 +243,7 @@ General dialogue, coding, multilingual quality, calibrated confidence, prompt-in
|
|
| 243 |
|
| 244 |
The selected BF16 weight file has **351,242,342 bytes** and the SHA-256 above. Original metadata and sanitized published metadata have separate identities in `checkpoint_provenance.json`. The source repository's snapshot verifier checks shipped code, tokenizer, docs and evidence; its native loader separately verifies the supplied weights.
|
| 245 |
|
| 246 |
-
The model card, metrics and technical report describe one fixed
|
| 247 |
|
| 248 |
## Licensing and source notices
|
| 249 |
|
|
|
|
| 21 |
- databricks/databricks-dolly-15k
|
| 22 |
---
|
| 23 |
|
| 24 |
+
# OpenSML-JSONLite-175M-Instruct
|
| 25 |
|
| 26 |
+
**Author:** William Zebrowski · **Model:** OpenSML-JSONLite-175M-Instruct · **Status:** private repository preparation / experimental extraction candidate
|
| 27 |
|
| 28 |
[Technical report](TECHNICAL_REPORT.md) · [Results](JSONLITE_RESULTS.json) · [Checkpoint provenance](checkpoint_provenance.json) · [Native inference verification](INFERENCE_VERIFICATION.json) · [Source repository](https://github.com/williamzebrowskI/OpenSML-JSONLite-175M)
|
| 29 |
|
|
|
|
| 86 |
## Training and model lineage
|
| 87 |
|
| 88 |
```text
|
| 89 |
+
Stage A pretrained/132005 → SFT-065/469 → SFT-068/379 → SFT-093/160
|
| 90 |
```
|
| 91 |
|
| 92 |
Only those selected stages are inherited. The many intervening research trials and failed RL/JSON experiments are not additional ancestors of the final weights.
|
|
|
|
| 140 |
|
| 141 |
The inherited post-training totals are **1,008 updates**, **32,243 presentations** and **5,646,323 serialized tokens**. These counts include repeated source views, and serialized token accounting includes prompt positions masked out of the loss.
|
| 142 |
|
| 143 |
+
All scores in this card describe the fixed model identified by the weight hash below. Detailed checkpoint history and reproducibility notes are recorded in the technical report and provenance file.
|
| 144 |
|
| 145 |
## Supported schema contract
|
| 146 |
|
|
|
|
| 189 |
|
| 190 |
### Complete-request correctness
|
| 191 |
|
| 192 |
+
| Panel | Parent SFT-068/379, same adapter | JSONLite-175M-Instruct |
|
| 193 |
| --- | --- | --- |
|
| 194 |
| Observed development | 139/196 — 70.92% | **168/196 — 85.71%** |
|
| 195 |
| Observed adapted SNIPS held-out | 953/1,388 — 68.66% | **1,132/1,388 — 81.56%** |
|
|
|
|
| 218 |
|
| 219 |
The held-out panel has 694 original source texts with two different requested-field views each, across seven SNIPS categories. Whole-request exact improves in every category under the same route, while present-field recall and false abstentions regress. The parent’s older **83.50% joint-labeled** test uses a different protocol and is not this table’s fieldwise JSON baseline.
|
| 220 |
|
| 221 |
+
The model fails the original strict per-category retention gates (`json_content_floor`, `json_vs_start`, `labeled_retention`, `qa_retention`). It is preserved at the owner's request as an experimental candidate; its automated release-ready flag remains false. Aggregate improvements do not erase these failures.
|
| 222 |
|
| 223 |
<details>
|
| 224 |
<summary>Protocol, metrics and evaluation independence</summary>
|
|
|
|
| 243 |
|
| 244 |
The selected BF16 weight file has **351,242,342 bytes** and the SHA-256 above. Original metadata and sanitized published metadata have separate identities in `checkpoint_provenance.json`. The source repository's snapshot verifier checks shipped code, tokenizer, docs and evidence; its native loader separately verifies the supplied weights.
|
| 245 |
|
| 246 |
+
The model card, metrics and technical report describe one fixed checkpoint. They do not include subsequent training. Clean-runtime 40-case parity is documented separately from the historical full-panel results. No automatic model updates, model promotion or hosted deployment is enabled.
|
| 247 |
|
| 248 |
## Licensing and source notices
|
| 249 |
|
SHA256SUMS
CHANGED
|
@@ -2,7 +2,7 @@
|
|
| 2 |
82b9908c9fd21fd8c9d10ad809e7c48446485ee98a56bfd9d64bf9fb353761c2 INFERENCE_VERIFICATION.json
|
| 3 |
d29cf5952a82db444a6df56446806b1f4e2ccbee1b4aa6b93cb7eeeabcab8536 JSONLITE_RESULTS.json
|
| 4 |
c71d239df91726fc519c6eb72d318ec65820627232b2f796219e87dcf35d0ab4 LICENSE
|
| 5 |
-
|
| 6 |
64519f25aded3e1fa74b0b9eafdf35df4490e7bb550027338a9bf1a25f9203bb SOURCE_NOTICE.md
|
| 7 |
4f8c90fad555e380c0e99b61582fe6f3bcb9e6f43a1f17d253769384471f8374 TECHNICAL_REPORT.md
|
| 8 |
423f0d1e0e2690505c24e6d31308db728fba60657c5166e177bb269d6a7198d0 THIRD_PARTY_NOTICES.md
|
|
|
|
| 2 |
82b9908c9fd21fd8c9d10ad809e7c48446485ee98a56bfd9d64bf9fb353761c2 INFERENCE_VERIFICATION.json
|
| 3 |
d29cf5952a82db444a6df56446806b1f4e2ccbee1b4aa6b93cb7eeeabcab8536 JSONLITE_RESULTS.json
|
| 4 |
c71d239df91726fc519c6eb72d318ec65820627232b2f796219e87dcf35d0ab4 LICENSE
|
| 5 |
+
0f6af13be03ee3e6896e76737f395e323e9690ad92ce41a1361cfb287544f838 README.md
|
| 6 |
64519f25aded3e1fa74b0b9eafdf35df4490e7bb550027338a9bf1a25f9203bb SOURCE_NOTICE.md
|
| 7 |
4f8c90fad555e380c0e99b61582fe6f3bcb9e6f43a1f17d253769384471f8374 TECHNICAL_REPORT.md
|
| 8 |
423f0d1e0e2690505c24e6d31308db728fba60657c5166e177bb269d6a7198d0 THIRD_PARTY_NOTICES.md
|