Instructions to use YakovElm/Hyperledger10_ElectraModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YakovElm/Hyperledger10_ElectraModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YakovElm/Hyperledger10_ElectraModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YakovElm/Hyperledger10_ElectraModel") model = AutoModelForSequenceClassification.from_pretrained("YakovElm/Hyperledger10_ElectraModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from YakovElm/Hyperledger10_ElectraModel: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/YakovElm/Hyperledger10_ElectraModel/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://YakovElm/Hyperledger10_ElectraModel/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/YakovElm/Hyperledger10_ElectraModel/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 240170b3c1e82f6d4b0fd03b97a819d223328b4eb01f8cf18e5c25504410d59d
- Size of remote file:
- 438 MB
- SHA256:
- 8c39d5cee9908fa14093449e26cef2c37e9b7bf47952e5ba2fb96c6f545fe99f
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