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matthewleechen
/
scientist_MP_classifier

Text Classification
Transformers
Safetensors
xlm-roberta
text-embeddings-inference
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xet
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How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-classification", model="matthewleechen/scientist_MP_classifier")
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("matthewleechen/scientist_MP_classifier")
model = AutoModelForSequenceClassification.from_pretrained("matthewleechen/scientist_MP_classifier", device_map="auto")
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This is a fine-tuned XLM-RoBERTa-large classifier trained to identify whether historical MPs in the British Parliament were scientists, anthropologists, explorers, or geographers, or came from such families.

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Model size
0.6B params
Tensor type
F32
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