Instructions to use simenaabol/tmp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simenaabol/tmp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="simenaabol/tmp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("simenaabol/tmp") model = AutoModelForSequenceClassification.from_pretrained("simenaabol/tmp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a72167ecd42c65a9e429ad0d087c8ccf1bb50b11ccfa7cfcfd46e5079bd38918
- Size of remote file:
- 498 MB
- SHA256:
- d52c5769db529208e42b8c7016121f5c6814614de5d4a49d95ee9e6a7e8440a6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.