Instructions to use grantpitt/autotagger with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use grantpitt/autotagger with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="grantpitt/autotagger")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("grantpitt/autotagger") model = AutoModel.from_pretrained("grantpitt/autotagger", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from grantpitt/autotagger: direct link, hf CLI and curl.
- Browser
- Download file 2.11 MB
-
https://huggingface.co/grantpitt/autotagger/resolve/main/tokenizer.json
- Command line
-
hf download hf://grantpitt/autotagger/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/grantpitt/autotagger/resolve/main/tokenizer.json
2.11 MB
File too large to display, you can check the raw version instead.