Instructions to use YakovElm/Hyperledger_20_BERT_More_Properties with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YakovElm/Hyperledger_20_BERT_More_Properties with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YakovElm/Hyperledger_20_BERT_More_Properties")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YakovElm/Hyperledger_20_BERT_More_Properties") model = AutoModelForSequenceClassification.from_pretrained("YakovElm/Hyperledger_20_BERT_More_Properties") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 15dd9ce8a25be7d9d964fa20297b261d3f38a3cd9c852db752a86f067b81af9a
- Size of remote file:
- 438 MB
- SHA256:
- 63520e9aebdca1dac13e7ad3caefeb91ec898e35f265a4310157965dd2511358
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