Text Classification
Transformers
PyTorch
Safetensors
English
roberta
cryptocurrency
crypto
BERT
sentiment classification
NLP
bitcoin
ethereum
shib
social media
sentiment analysis
cryptocurrency sentiment analysis
text-embeddings-inference
Instructions to use ElKulako/cryptobert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ElKulako/cryptobert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ElKulako/cryptobert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ElKulako/cryptobert") model = AutoModelForSequenceClassification.from_pretrained("ElKulako/cryptobert") - Inference
- Notebooks
- Google Colab
- Kaggle
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datasets:
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- ElKulako/stocktwits-crypto
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language:
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- en
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tags:
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- cryptocurrency
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- social media
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- sentiment analysis
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- cryptocurrency sentiment analysis
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---
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For academic reference, cite the following paper: https://ieeexplore.ieee.org/document/10223689
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---
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datasets:
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- ElKulako/stocktwits-crypto
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language:
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- en
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tags:
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- cryptocurrency
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- social media
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- sentiment analysis
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- cryptocurrency sentiment analysis
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license: mit
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---
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For academic reference, cite the following paper: https://ieeexplore.ieee.org/document/10223689
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