Instructions to use natankatz/chan_model_class111 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use natankatz/chan_model_class111 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="natankatz/chan_model_class111")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("natankatz/chan_model_class111") model = AutoModelForSequenceClassification.from_pretrained("natankatz/chan_model_class111") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec6fc19c424ff80c3289379d55d448916e57baf8965ebea16cb7ef1212c78630
- Size of remote file:
- 444 MB
- SHA256:
- 1aa7233eccea3c09115f58024cb6fc79acab67b06c20785133f82a7b59d1bdf8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.