Instructions to use Mariaaaaa/checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mariaaaaa/checkpoints with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mariaaaaa/checkpoints")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mariaaaaa/checkpoints") model = AutoModelForSequenceClassification.from_pretrained("Mariaaaaa/checkpoints") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ed23b0bce775765a8763f79bd9fd15e40008292b212aba7185f864884d5e41b1
- Size of remote file:
- 17.5 MB
- SHA256:
- c087f92c89fb34ecd55ac65bd9d9d391513e79a359c7cc035c159f654476c25c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.