Instructions to use LogicSpine/address-base-text-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LogicSpine/address-base-text-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="LogicSpine/address-base-text-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LogicSpine/address-base-text-classifier") model = AutoModelForSequenceClassification.from_pretrained("LogicSpine/address-base-text-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-1356/optimizer.pt from LogicSpine/address-base-text-classifier: direct link, hf CLI and curl.
- Browser
- Download file 997 MB
-
https://huggingface.co/LogicSpine/address-base-text-classifier/resolve/main/checkpoint-1356/optimizer.pt
- Command line
-
hf download hf://LogicSpine/address-base-text-classifier/checkpoint-1356/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/LogicSpine/address-base-text-classifier/resolve/main/checkpoint-1356/optimizer.pt
997 MB
- Xet hash:
- 883e567f7d72ceae6ff6c8e1b25b03011ce3d8234f22eadf2af71ff209da1072
- Size of remote file:
- 997 MB
- SHA256:
- 51273394b98b3d3b157da0e2b930c7faa17c5ad57750cca56ceacf8026525a78
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