Instructions to use alvarodt/geocoding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alvarodt/geocoding with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="alvarodt/geocoding")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("alvarodt/geocoding") model = AutoModel.from_pretrained("alvarodt/geocoding", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from alvarodt/geocoding: direct link, hf CLI and curl.
- Browser
- Download file 236 MB
-
https://huggingface.co/alvarodt/geocoding/resolve/b56ca3f56644e330ce940f522611eba333717df9/pytorch_model.bin
- Command line
-
hf download hf://alvarodt/geocoding@b56ca3f56644e330ce940f522611eba333717df9/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/alvarodt/geocoding/resolve/b56ca3f56644e330ce940f522611eba333717df9/pytorch_model.bin
236 MB
- Xet hash:
- d81910394d13d6a2c894af186dc8a405cd2602b2f4331213e918245c33d0d303
- Size of remote file:
- 236 MB
- SHA256:
- 35fef21301d7446fcd9f34bf11129a59cdfc72e9317295bbfd242f5679d16067
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.