Instructions to use CrisisNarratives/adapter-8classes-multi_label with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CrisisNarratives/adapter-8classes-multi_label with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("CrisisNarratives/adapter-8classes-multi_label") model = AutoModelForMultimodalLM.from_pretrained("CrisisNarratives/adapter-8classes-multi_label") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a4ae38f362019f36d515920dfa269e1a9b255732eb320c049052ec668c6a9876
- Size of remote file:
- 899 MB
- SHA256:
- ea68f4d9e96b554aca884b5f7a4a93f4ed12a50fabdee4d9c30af049aca6082e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.