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
Upload model
Browse files- config.json +2 -2
- pytorch_model.bin +2 -2
config.json
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{
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"activation": "
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"architectures": [
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"DistilBertModel"
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],
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"max_position_embeddings": 512,
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"model_type": "distilbert",
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"n_heads": 12,
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"n_layers":
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"pad_token_id": 0,
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"qa_dropout": 0.1,
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"seq_classif_dropout": 0.2,
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{
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"activation": "gelu",
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"architectures": [
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"DistilBertModel"
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],
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"max_position_embeddings": 512,
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"model_type": "distilbert",
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"n_heads": 12,
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"n_layers": 4,
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"pad_token_id": 0,
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"qa_dropout": 0.1,
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"seq_classif_dropout": 0.2,
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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version https://git-lfs.github.com/spec/v1
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size 208771005
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