Instructions to use efederici/bertflow-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use efederici/bertflow-it with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="efederici/bertflow-it")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("efederici/bertflow-it") model = AutoModel.from_pretrained("efederici/bertflow-it") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d9fa02b0936550ac8d4aa8cf534d4b8923c1c0d6ec00042b9e98580670bf2375
- Size of remote file:
- 443 MB
- SHA256:
- 531b4c4460ab19892ec514ec180e7960df2d166154604e14cb733274f6987236
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.