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gsstec/aegis-scibert-technical

sourceHugging Facemitupdated 9mo agoView on Hugging Face
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AEGIS SciBERT Technical Classifier

Model Description

Fine-tuned SciBERT model for classifying technical papers into research categories.

Training Details

  • —Base Model: allenai/scibertscivocabuncased
  • —Training Samples: 500
  • —Number of Classes: 6
  • —Classes: cs.AI, cs.LG, quant-ph, cs.NE, stat.ML, cs.CV
  • —Validation Accuracy: 1.0000

Usage

python
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("gsstec/aegis-scibert-technical")
tokenizer = AutoTokenizer.from_pretrained("gsstec/aegis-scibert-technical")

# Example inference
text = "Quantum computing algorithms for machine learning"
inputs = tokenizer(text, return_tensors="pt")
outputs = model(**inputs)
predictions = torch.softmax(outputs.logits, dim=-1)

Classes

  • —cs.AI: Class 0
  • —cs.LG: Class 1
  • —quant-ph: Class 2
  • —cs.NE: Class 3
  • —stat.ML: Class 4
  • —cs.CV: Class 5