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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ElKulako/cryptobert") model = AutoModelForSequenceClassification.from_pretrained("ElKulako/cryptobert", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ElKulako/cryptobert: direct link, hf CLI and curl.
- Browser
- Download file 2.11 MB
-
https://huggingface.co/ElKulako/cryptobert/resolve/main/tokenizer.json
- Command line
-
hf download hf://ElKulako/cryptobert/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ElKulako/cryptobert/resolve/main/tokenizer.json
2.11 MB
File too large to display, you can check the raw version instead.