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:
- e599ae9b095314fb076f704b1433f860f4feaf2bcd0c1f03583d150765967386
- Size of remote file:
- 3.39 kB
- SHA256:
- 97281d01c83ea6aa8ae8b14189710bf1bd2535bb0fcd75be28b149b3e6777311
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