Instructions to use YakovElm/Jira5_ElectraModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YakovElm/Jira5_ElectraModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YakovElm/Jira5_ElectraModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YakovElm/Jira5_ElectraModel") model = AutoModelForSequenceClassification.from_pretrained("YakovElm/Jira5_ElectraModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from YakovElm/Jira5_ElectraModel: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/YakovElm/Jira5_ElectraModel/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://YakovElm/Jira5_ElectraModel/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/YakovElm/Jira5_ElectraModel/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- e1e4efdde3eb14d68b8f4ccc423fcbee7a8d11711b94d0ec564372d818ab200f
- Size of remote file:
- 438 MB
- SHA256:
- 5ab3b4881b002f799384fb21674158621dc6be46c335d9e428744cc5ed06691d
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