Instructions to use YakovElm/Jira10_ElectraModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YakovElm/Jira10_ElectraModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YakovElm/Jira10_ElectraModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YakovElm/Jira10_ElectraModel") model = AutoModelForSequenceClassification.from_pretrained("YakovElm/Jira10_ElectraModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from YakovElm/Jira10_ElectraModel: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/YakovElm/Jira10_ElectraModel/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://YakovElm/Jira10_ElectraModel/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/YakovElm/Jira10_ElectraModel/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 99eb2faa7bd2bbb33997a4a999cb8aee3becd97a05a2c01d36088d8db1ef9f00
- Size of remote file:
- 438 MB
- SHA256:
- 9049c5a74c10f1981ebe2b352252c4598a5939392586b9583de51143c1745763
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