Text Classification
Transformers
PyTorch
Safetensors
English
bert
Generated from Trainer
crypto
sentiment
analysis
text-embeddings-inference
Instructions to use kk08/CryptoBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kk08/CryptoBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kk08/CryptoBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kk08/CryptoBERT") model = AutoModelForSequenceClassification.from_pretrained("kk08/CryptoBERT") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd6f340e94dd1db1fd332fc6bac58f87548d18eb80e739a35a2dd8d94d3c52eb
- Size of remote file:
- 438 MB
- SHA256:
- 0f636a193c5e056fca4e59a798013ea4e31d2d591026d069e77797883342ad86
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