Instructions to use YakovElm/Hyperledger20Classic_MSE_Sample with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YakovElm/Hyperledger20Classic_MSE_Sample with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YakovElm/Hyperledger20Classic_MSE_Sample")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YakovElm/Hyperledger20Classic_MSE_Sample") model = AutoModelForSequenceClassification.from_pretrained("YakovElm/Hyperledger20Classic_MSE_Sample") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d246e544473ff73ae9088a1297a82e2204b119bcc4cbaf9d543bceccf3c939d8
- Size of remote file:
- 438 MB
- SHA256:
- dbc0a85db0c944672e0e64e9020388c8affdc5f007696c4763b8e8952141007b
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