Instructions to use hugo/secret-project-ms-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hugo/secret-project-ms-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hugo/secret-project-ms-2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hugo/secret-project-ms-2") model = AutoModelForSequenceClassification.from_pretrained("hugo/secret-project-ms-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0aba6e52a42e937f8c191cae72a2924d45c9c117a2799ea27d234eb2b0016632
- Size of remote file:
- 90.9 MB
- SHA256:
- ca5e17f8fa819421e49f096a8dd6cade327825ee73378a6ef1e8341675edbe62
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.