Token Classification
Transformers
PyTorch
Safetensors
English
bert
toponym detection
language model
geospatial understanding
geolm
Instructions to use knowledge-computing/geolm-base-toponym-recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use knowledge-computing/geolm-base-toponym-recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="knowledge-computing/geolm-base-toponym-recognition")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("knowledge-computing/geolm-base-toponym-recognition") model = AutoModelForTokenClassification.from_pretrained("knowledge-computing/geolm-base-toponym-recognition") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +0 -1
config.json
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"num_semantic_types": 97,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"torch_dtype": "float32",
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"torch_dtype": "float32",
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