Instructions to use LogicSpine/address-large-text-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LogicSpine/address-large-text-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="LogicSpine/address-large-text-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LogicSpine/address-large-text-classifier") model = AutoModelForSequenceClassification.from_pretrained("LogicSpine/address-large-text-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-85566/optimizer.pt from LogicSpine/address-large-text-classifier: direct link, hf CLI and curl.
- Browser
- Download file 997 MB
-
https://huggingface.co/LogicSpine/address-large-text-classifier/resolve/main/checkpoint-85566/optimizer.pt
- Command line
-
hf download hf://LogicSpine/address-large-text-classifier/checkpoint-85566/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/LogicSpine/address-large-text-classifier/resolve/main/checkpoint-85566/optimizer.pt
997 MB
- Xet hash:
- 7c4e46a9373f04de889b57f834dbf9cc815af6e2f65db3e18334585a45a801a8
- Size of remote file:
- 997 MB
- SHA256:
- 3f1ac457545db1f44ff3ea44ea8d5b477777ad7694b5cacb76e008fb3a2cc07f
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