Text Classification
Transformers
Joblib
ONNX
Safetensors
English
bert
masterformat
masterformat-classifier
csi-masterformat
construction
construction-technology
sequence-classification
tfidf
ensemble
specs
spec-writing
specifications
takeoff
estimating
cost-code
ufgs
public-domain
Eval Results (legacy)
text-embeddings-inference
Instructions to use constructelligence/masterformat-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use constructelligence/masterformat-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="constructelligence/masterformat-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("constructelligence/masterformat-classifier") model = AutoModelForSequenceClassification.from_pretrained("constructelligence/masterformat-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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# MasterFormat classifier (mf-0.2) — construction spec & line-item classification
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A BERT text classifier that maps **construction line items, specification paragraphs, submittals and
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section titles** to one of **171 MasterFormat level-2 groups** (e.g. `03 30 00 Cast-in-Place Concrete`,
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`23 30 00 HVAC Air Distribution`) across **32 divisions**. It is the machine-learning counterpart to a
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# MasterFormat classifier (mf-0.2) — construction spec & line-item classification
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> **Constructelligence is developing frontier construction-AI models.** This classifier is the *lite*, open
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> tier — released for research and evaluation; the company's flagship production models are a separate,
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> larger tier (see [constructelligence.co](https://constructelligence.co)).
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A BERT text classifier that maps **construction line items, specification paragraphs, submittals and
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section titles** to one of **171 MasterFormat level-2 groups** (e.g. `03 30 00 Cast-in-Place Concrete`,
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`23 30 00 HVAC Air Distribution`) across **32 divisions**. It is the machine-learning counterpart to a
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