Instructions to use ThomasKaspereit/IAS40BERT-extval with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThomasKaspereit/IAS40BERT-extval with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ThomasKaspereit/IAS40BERT-extval")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ThomasKaspereit/IAS40BERT-extval") model = AutoModelForSequenceClassification.from_pretrained("ThomasKaspereit/IAS40BERT-extval", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1b45f75793cf4f0089f1071f4ac813023d3eb33772601a274626764064b96154
- Size of remote file:
- 4.98 kB
- SHA256:
- c0f25ace166a96835ca77753d94b6f671de631bb284f26a22e3fb1b74f5d4e0e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.