Instructions to use Kaspar/bert_ecco_ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kaspar/bert_ecco_ft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Kaspar/bert_ecco_ft")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Kaspar/bert_ecco_ft") model = AutoModelForMaskedLM.from_pretrained("Kaspar/bert_ecco_ft") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 98be979f39170c2ce11cb0a928e214231f9a3db633253c663c278cb096475447
- Size of remote file:
- 5.84 kB
- SHA256:
- 061a7724aba33366be45beb603207c7c7c8b44d55aec1e3e187aa70dce78cdca
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.