Instructions to use boronbrown48/1_topic_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use boronbrown48/1_topic_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="boronbrown48/1_topic_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("boronbrown48/1_topic_classification") model = AutoModelForSequenceClassification.from_pretrained("boronbrown48/1_topic_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from boronbrown48/1_topic_classification: direct link, hf CLI and curl.
- Browser
- Download file 421 MB
-
https://huggingface.co/boronbrown48/1_topic_classification/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://boronbrown48/1_topic_classification/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/boronbrown48/1_topic_classification/resolve/main/pytorch_model.bin
421 MB
- Xet hash:
- dddc2c8d0066f3b2adac2c0b5c00371841c0049ebd5244c13bdcb96ad6b03cae
- Size of remote file:
- 421 MB
- SHA256:
- 98eed6b5fe0ccec7a677611960371e511638ac71fd9201c8fb90a8f86847bd84
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