Instructions to use levshechter/tibetan_code_switching_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use levshechter/tibetan_code_switching_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="levshechter/tibetan_code_switching_model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("levshechter/tibetan_code_switching_model") model = AutoModelForTokenClassification.from_pretrained("levshechter/tibetan_code_switching_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
0f8ea01 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:6c9fb47a1b9e042c718e44870c1361222e36ba6ae11efa25444ce8a3e43c2492
size 5240
|