Zero-Shot Classification
Transformers
Safetensors
GGUF
English
decision-model
system-one
falcondec
lightdec
calibrated-decisions
multiple-choice
intent-classification
customer-support
natural-language-inference
code
guardrails
agents
selective-prediction
falconsai
model-surgeon
attested-lineage
Instructions to use Falconsai/LightDec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Falconsai/LightDec with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="Falconsai/LightDec")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Falconsai/LightDec", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
CHANGED
|
@@ -20,14 +20,17 @@ tags:
|
|
| 20 |
- agents
|
| 21 |
- selective-prediction
|
| 22 |
- falconsai
|
|
|
|
|
|
|
| 23 |
---
|
|
|
|
| 24 |
> Source model card: `Falconsai/LightDec` @ `main`, carried verbatim below. Its licence is the repository's. The Model Surgeon record follows it.
|
| 25 |
|
|
|
|
| 26 |
|
| 27 |
|
| 28 |
-
# Falconsai/LightDec
|
| 29 |
|
| 30 |
-
|
| 31 |
|
| 32 |
**A lightweight, single-pass, typed, calibrated decision model for agentic systems.** Give it a **state** (text, code or JSON), one or more **typed questions** (`choice`, `noul` yes/no, `score` ordinal) and a closed set of options. It returns a calibrated probability for every option, from one encoder pass per question.
|
| 33 |
|
|
@@ -1012,3 +1015,50 @@ This is evidence, not legal advice.
|
|
| 1012 |
*Operated with Model Surgeon — verify this package at https://surgeon.falcons.ai/verify*
|
| 1013 |
*© 2026 FALCONS.AI — Model Surgeon record format. The model weights remain their owner's.*
|
| 1014 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 20 |
- agents
|
| 21 |
- selective-prediction
|
| 22 |
- falconsai
|
| 23 |
+
- model-surgeon
|
| 24 |
+
- attested-lineage
|
| 25 |
---
|
| 26 |
+
|
| 27 |
> Source model card: `Falconsai/LightDec` @ `main`, carried verbatim below. Its licence is the repository's. The Model Surgeon record follows it.
|
| 28 |
|
| 29 |
+
> Source model card: `Falconsai/LightDec` @ `main`, carried verbatim below. Its licence is the repository's. The Model Surgeon record follows it.
|
| 30 |
|
| 31 |
|
|
|
|
| 32 |
|
| 33 |
+
# Falconsai/LightDec
|
| 34 |
|
| 35 |
**A lightweight, single-pass, typed, calibrated decision model for agentic systems.** Give it a **state** (text, code or JSON), one or more **typed questions** (`choice`, `noul` yes/no, `score` ordinal) and a closed set of options. It returns a calibrated probability for every option, from one encoder pass per question.
|
| 36 |
|
|
|
|
| 1015 |
*Operated with Model Surgeon — verify this package at https://surgeon.falcons.ai/verify*
|
| 1016 |
*© 2026 FALCONS.AI — Model Surgeon record format. The model weights remain their owner's.*
|
| 1017 |
|
| 1018 |
+
---
|
| 1019 |
+
|
| 1020 |
+
# Model Card — Falconsai/LightDec/
|
| 1021 |
+
|
| 1022 |
+
**[View in Model Surgeon](https://surgeon.falcons.ai/?hub=Falconsai/LightDec)**
|
| 1023 |
+
|
| 1024 |
+
**[View in Model Surgeon](https://surgeon.falcons.ai/?hub=Falconsai/LightDec)**
|
| 1025 |
+
|
| 1026 |
+
This card is generated from the surgical record itself; the package's
|
| 1027 |
+
`lineage.intoto.jsonl` is the signed source of truth (verify it free at
|
| 1028 |
+
the Surgeon's public verifier or with the bundled `verify_attestation.py`).
|
| 1029 |
+
|
| 1030 |
+
## Architecture
|
| 1031 |
+
- Identification: **NLP · Small Language Model (SLM)** (98% confidence)
|
| 1032 |
+
- Source format: `safetensors` · Intended task: not declared
|
| 1033 |
+
- `config.json`: synthesized from the anatomy (no source config.json); model_type omitted — no architecture name in the source (QA-F-126)
|
| 1034 |
+
- Source license: apache-2.0
|
| 1035 |
+
- Lineage chain: 1 surgery (no prior attestation reachable) · Falconsai/LightDec
|
| 1036 |
+
- Post-surgery totals: 159,654,157 parameters ·
|
| 1037 |
+
168 tensors
|
| 1038 |
+
- Compute estimate: 15.02439 GFLOPs (comparison
|
| 1039 |
+
metric, not a measurement)
|
| 1040 |
+
|
| 1041 |
+
## Provenance & operations
|
| 1042 |
+
- Parents: Falconsai/LightDec/model.safetensors
|
| 1043 |
+
- Operations performed: load×1
|
| 1044 |
+
- Weight merges recorded: 0
|
| 1045 |
+
- Quantized tensors (F32→F16): 0
|
| 1046 |
+
|
| 1047 |
+
## Surgery Log (ordered)
|
| 1048 |
+
1. **load** — hub:Falconsai/LightDec/model.safetensors (319.3 MB, safetensors)
|
| 1049 |
+
|
| 1050 |
+
## Validation
|
| 1051 |
+
- Tissue imaging: not run
|
| 1052 |
+
- Structural integrity is testable offline via the packaged
|
| 1053 |
+
`load_and_test.py`.
|
| 1054 |
+
|
| 1055 |
+
## Compliance note
|
| 1056 |
+
The signed attestation + this card together document model composition,
|
| 1057 |
+
modification history, and validation evidence — the record structure
|
| 1058 |
+
technical-documentation obligations (e.g. EU AI Act Annex IV) ask for.
|
| 1059 |
+
This is evidence, not legal advice.
|
| 1060 |
+
|
| 1061 |
+
---
|
| 1062 |
+
*Operated with Model Surgeon — verify this package at https://surgeon.falcons.ai/verify*
|
| 1063 |
+
*© 2026 FALCONS.AI — Model Surgeon record format. The model weights remain their owner's.*
|
| 1064 |
+
|