Instructions to use linkdata/text_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use linkdata/text_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="linkdata/text_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("linkdata/text_classification") model = AutoModelForSeq2SeqLM.from_pretrained("linkdata/text_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e4fa33f0d18bcfc944fd47c236904ec5d641c916d9cd435e12e4d59004fd1521
- Size of remote file:
- 5.24 kB
- SHA256:
- d3622d96d2db96cf8711753cb972d21d4e8d0f621a5acc383b5c3172dabe46e0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.