Instructions to use spentaur/post-here with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use spentaur/post-here with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="spentaur/post-here")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("spentaur/post-here") model = AutoModelForSequenceClassification.from_pretrained("spentaur/post-here", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from spentaur/post-here: direct link, hf CLI and curl.
- Browser
- Download file 1.84 kB
-
https://huggingface.co/spentaur/post-here/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://spentaur/post-here@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/spentaur/post-here/resolve/refs%2Fpr%2F1/training_args.bin
1.84 kB
- Xet hash:
- bb1e80e00495199331a8aed21975799cb5e9158c4fe1096f88bd0fa77f7d242c
- Size of remote file:
- 1.84 kB
- SHA256:
- d9b997c9bde0acbb53bd0d65655ce751153292f976bb21b6c82a140eef5beaa4
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