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 training_args.bin from scroobiustrip/topic-classifier-v2: direct link, hf CLI and curl.
- Browser
- Download file 3.9 kB
-
https://huggingface.co/scroobiustrip/topic-classifier-v2/resolve/main/training_args.bin
- Command line
-
hf download hf://scroobiustrip/topic-classifier-v2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/scroobiustrip/topic-classifier-v2/resolve/main/training_args.bin
3.9 kB
- Xet hash:
- 95692f8a9658e5926a7dbbaee1c152e1dada9525c64d9bd425f6dc836bcad996
- Size of remote file:
- 3.9 kB
- SHA256:
- 739a8d9091a6a467d12db7e7ff3c876fc99d8506ab45c21dbf57a8b5a365872a
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