Instructions to use nz/RITA_m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nz/RITA_m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="nz/RITA_m", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("nz/RITA_m", trust_remote_code=True) model = AutoModel.from_pretrained("nz/RITA_m", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 55bba45e724ecc2274abddb716ee128657273bb8a9bb66ebd21425dc51934d40
- Size of remote file:
- 605 MB
- SHA256:
- fc039b6a04138c3b5c42a7a3bff8f3dfef5f54ec5dca90cc777909c35bc12a44
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