Instructions to use CodeNinja1126/test-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CodeNinja1126/test-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CodeNinja1126/test-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CodeNinja1126/test-model") model = AutoModelForSequenceClassification.from_pretrained("CodeNinja1126/test-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f727bc4ad9bbe9ae8b3cf8ef52f88933f7c3842e981fbe829d5fffadd986c019
- Size of remote file:
- 712 MB
- SHA256:
- b3cfb7963bec5a52f438ae00572a362fb8a46836b2c991f7098b6a7b2fe1951c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.