Instructions to use junwon28/lang6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use junwon28/lang6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="junwon28/lang6")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("junwon28/lang6") model = AutoModelForSequenceClassification.from_pretrained("junwon28/lang6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a287632addc337db6bb4bf75f9da98a246cde81a15c9bff08dd772719d91c70
- Size of remote file:
- 452 MB
- SHA256:
- a3d444e98b6d2b6e34475cdbe8e60f95a0eb4acf997b91710d82ae7c4b60d543
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.