Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use azamat/geocoder_relevancy_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use azamat/geocoder_relevancy_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="azamat/geocoder_relevancy_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("azamat/geocoder_relevancy_model") model = AutoModelForSequenceClassification.from_pretrained("azamat/geocoder_relevancy_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44ee9ff6d3aba96fb132e8f486ddfc009881059129115d805cb6c9d20eafe603
- Size of remote file:
- 3.39 kB
- SHA256:
- 581dabffef33d82b3c62df5af18db279db9eb9c57828e299cc8c483910e27dda
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