Instructions to use YakovElm/MariaDB10_ElectraModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YakovElm/MariaDB10_ElectraModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YakovElm/MariaDB10_ElectraModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YakovElm/MariaDB10_ElectraModel") model = AutoModelForSequenceClassification.from_pretrained("YakovElm/MariaDB10_ElectraModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from YakovElm/MariaDB10_ElectraModel: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/YakovElm/MariaDB10_ElectraModel/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://YakovElm/MariaDB10_ElectraModel/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/YakovElm/MariaDB10_ElectraModel/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 111af9c9a3a109d6b79b097f7c0c4abe73aa01e70306ffd2ef2f50d85af93a30
- Size of remote file:
- 438 MB
- SHA256:
- c75dc5df5493646f0c38ccb1e5a462d9e68ba698646c9a1c7809e826dfcf04bb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.