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 pytorch_model.bin from spentaur/post-here: direct link, hf CLI and curl.
- Browser
- Download file 557 MB
-
https://huggingface.co/spentaur/post-here/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://spentaur/post-here/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/spentaur/post-here/resolve/main/pytorch_model.bin
557 MB
- Xet hash:
- b0099c28d4104c6a81233447943a8bc4d4baf1145f85b2b95c717c2f428f2495
- Size of remote file:
- 557 MB
- SHA256:
- 1e9bc313961d73841061d54fa941c13933f7934bd922891f73a2b0ae12b0252b
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