Instructions to use 0xMaka/based-bert-sc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 0xMaka/based-bert-sc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="0xMaka/based-bert-sc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("0xMaka/based-bert-sc") model = AutoModelForSequenceClassification.from_pretrained("0xMaka/based-bert-sc") - Notebooks
- Google Colab
- Kaggle
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Browse files
README.md
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---
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datasets:
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- 0xMaka/trading-candles-subset-sc-format
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language:
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- en
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metrics:
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- accuracy
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- f1
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widget:
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- text: "identify candle: open: 17343.43, close: 17625.18, high: 17804.68, low: 17322.15"
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example_title: "Sequence classification"
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- text: "identify candle: 17284.58,17264.41,17284.58,17264.41"
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example_title: "Sequence classification"
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---
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# Based Bert
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