Instructions to use Iariaf/joy_multilang with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Iariaf/joy_multilang with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Iariaf/joy_multilang")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Iariaf/joy_multilang") model = AutoModelForSequenceClassification.from_pretrained("Iariaf/joy_multilang", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 589b63b036be98c4dc44a5121ffb8b669122d05bb30a7d340cd2e354b6f4dfe4
- Size of remote file:
- 134 MB
- SHA256:
- 0f98b76ac0466d3638dc3f612729aa87e961b10ad8fd75b28b9b66b83a1a370f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.