Instructions to use vargr/yt-openloop-quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vargr/yt-openloop-quantized with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vargr/yt-openloop-quantized")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vargr/yt-openloop-quantized") model = AutoModelForSequenceClassification.from_pretrained("vargr/yt-openloop-quantized") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3a15d7ff46e9b20c9ddba7efd41f38795b84731db04d5adbcadc9332c625065e
- Size of remote file:
- 110 MB
- SHA256:
- 17bd5ff32cf8e630990bbd3c01dea3bc0080ce14312cecaed5b861704ae5af01
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.