Instructions to use TransQuest/monotransquest-da-multilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TransQuest/monotransquest-da-multilingual with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TransQuest/monotransquest-da-multilingual")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TransQuest/monotransquest-da-multilingual") model = AutoModelForSequenceClassification.from_pretrained("TransQuest/monotransquest-da-multilingual") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f2a13359326de25af0c0f4e626510c8d59d0b39723f37044220802f30ad67c5d
- Size of remote file:
- 2.24 GB
- SHA256:
- 29a93eaa57a6357c23668b72c590066a52a5adaf940ff1b8777bf27f713131e5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.