Instructions to use superman/testingmodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use superman/testingmodel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="superman/testingmodel")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("superman/testingmodel") model = AutoModelForTokenClassification.from_pretrained("superman/testingmodel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0ab63238b01e5e462903c68cecd8d439eae1a5304a8467688cf4318cf5c91574
- Size of remote file:
- 431 MB
- SHA256:
- 1f923c534417e6a91acae1ebad80438162420da58c9baa1b684b623633bb1cae
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.