Instructions to use Elron/bleurt-base-128 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Elron/bleurt-base-128 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Elron/bleurt-base-128")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Elron/bleurt-base-128") model = AutoModelForSequenceClassification.from_pretrained("Elron/bleurt-base-128", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Elron/bleurt-base-128: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/Elron/bleurt-base-128/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Elron/bleurt-base-128/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Elron/bleurt-base-128/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 7e42e1be4500b48e0b5a3ac8b8f96c19ac8cdcbaa6eb4d8aef8ea3b4edb6ce83
- Size of remote file:
- 438 MB
- SHA256:
- 9b0b9f3e83533c77a2ace759734ba2c0f5ac494c88018df701705f4d3c2e259e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.