Instructions to use arj9719/robertuito_topic_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arj9719/robertuito_topic_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="arj9719/robertuito_topic_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("arj9719/robertuito_topic_classification") model = AutoModelForSequenceClassification.from_pretrained("arj9719/robertuito_topic_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from arj9719/robertuito_topic_classification: direct link, hf CLI and curl.
- Browser
- Download file 435 MB
-
https://huggingface.co/arj9719/robertuito_topic_classification/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://arj9719/robertuito_topic_classification/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/arj9719/robertuito_topic_classification/resolve/main/pytorch_model.bin
435 MB
- Xet hash:
- 276689e4eb151fcbebe4779902002748d64daf7e5ed33a654f3a427591c34462
- Size of remote file:
- 435 MB
- SHA256:
- cb8d9ce5d48505874aff1aa6b0769b8fbda04f40a0f59ebbd6a595ff8da46329
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