Instructions to use k4tel/bert-multilingial-geolocation-prediction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use k4tel/bert-multilingial-geolocation-prediction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="k4tel/bert-multilingial-geolocation-prediction")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("k4tel/bert-multilingial-geolocation-prediction") model = AutoModelForMaskedLM.from_pretrained("k4tel/bert-multilingial-geolocation-prediction") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a7d9c7e4f894e4e05e9d977c75ffd2c4bc0e43de14d35dace2a39be415c3fa7
- Size of remote file:
- 3.44 kB
- SHA256:
- 9dc97d396090beb42dfca5d04f497c9e78264abdd99f6138810761fe861c8218
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.