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
Commit History
13 days ago
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Upgrade ensemble to word+char TF-IDF: line-item 0.686->0.702, section 0.613->0.620 (weights chosen on val)
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14 days ago
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Add transformer+TF-IDF ensemble (line-item top-1 0.597 -> 0.686) and document it in the card
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Publish mf-0.2: completed GPU fine-tune (val 46.6%, 2.3x mf-0.1) + new model card with metrics/ONNX
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Improve model card (SEO title, FAQ, citation, widgets) and add predict.py CLI, CITATION.cff, requirements.txt
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18 days ago
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Upload mf-0.1
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initial commit
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