Instructions to use Delphia/twitter-spam-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Delphia/twitter-spam-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Delphia/twitter-spam-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Delphia/twitter-spam-classifier") model = AutoModelForSequenceClassification.from_pretrained("Delphia/twitter-spam-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-60/optimizer.pt from Delphia/twitter-spam-classifier: direct link, hf CLI and curl.
- Browser
- Download file 876 MB
-
https://huggingface.co/Delphia/twitter-spam-classifier/resolve/main/checkpoint-60/optimizer.pt
- Command line
-
hf download hf://Delphia/twitter-spam-classifier/checkpoint-60/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Delphia/twitter-spam-classifier/resolve/main/checkpoint-60/optimizer.pt
876 MB
- Xet hash:
- c0db2e48c4949ec1d4a96c7700a0f0e9a61b1b42e1a9e960ceecc9c3a8ec3c2a
- Size of remote file:
- 876 MB
- SHA256:
- 4a53dc85f6b437bc5653d111d97c65f400a899764dba72e370e66aa7c6ebdb38
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