Instructions to use scroobiustrip/topic-classifier-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scroobiustrip/topic-classifier-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="scroobiustrip/topic-classifier-v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("scroobiustrip/topic-classifier-v2") model = AutoModelForSequenceClassification.from_pretrained("scroobiustrip/topic-classifier-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from scroobiustrip/topic-classifier-v2: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/scroobiustrip/topic-classifier-v2/resolve/main/tokenizer.json
- Command line
-
hf download hf://scroobiustrip/topic-classifier-v2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/scroobiustrip/topic-classifier-v2/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 404c1fb20a18ec02bbdabd1da6867e5ba3697b979a2a24b3c7ad976546572665
- Size of remote file:
- 17.1 MB
- SHA256:
- f2c509a525eb51aebb33fb59c24ee923c1d4c1db23c3ae81fe05ccf354084f7b
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