Text Classification
Transformers
PyTorch
TensorBoard
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use azamat/geocoder_coordinates_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use azamat/geocoder_coordinates_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="azamat/geocoder_coordinates_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("azamat/geocoder_coordinates_model") model = AutoModelForSequenceClassification.from_pretrained("azamat/geocoder_coordinates_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- decba82a7ffdbbbce0baab40bad6e053351db5a707553a5cd18b35f814d01ba5
- Size of remote file:
- 3.31 kB
- SHA256:
- 1985e86cb6b2a2dc955d6949ad6c327f914fb4ee9f44bd6ff282c27fe58aa630
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