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
File size: 844 Bytes
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title: "MasterFormat Classifier (mf-0.2)"
message: "If you use this model, please cite it as below."
type: software
authors:
- name: "Constructelligence"
website: "https://constructelligence.co"
license: MIT
url: "https://huggingface.co/constructelligence/masterformat-classifier"
repository-code: "https://huggingface.co/constructelligence/masterformat-classifier"
abstract: >-
A BERT-based text classifier that maps construction line items, specification
paragraphs and section titles to one of 171 MasterFormat level-2 groups across
32 divisions. Fine-tuned from BAAI/bge-small-en-v1.5 on public-domain UFGS
specification text. mf-0.2 is the completed 12-epoch GPU fine-tune.
keywords:
- MasterFormat
- construction
- text-classification
- specifications
- estimating
- takeoff
- UFGS
- BERT
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