Text Classification
Transformers
Safetensors
English
bert
multilabel
classification
finetune
finance
regulatory
text
risk
text-embeddings-inference
Instructions to use yirifiai1/BERT_Regulatory_Text_Classification_01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yirifiai1/BERT_Regulatory_Text_Classification_01 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yirifiai1/BERT_Regulatory_Text_Classification_01")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yirifiai1/BERT_Regulatory_Text_Classification_01") model = AutoModelForSequenceClassification.from_pretrained("yirifiai1/BERT_Regulatory_Text_Classification_01") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer
Browse files- tokenizer.json +16 -2
tokenizer.json
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"truncation": {
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"direction": "Right",
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"max_length": 128,
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"strategy": "LongestFirst",
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"direction": "Right",
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"pad_token": "[PAD]"
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"added_tokens": [
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