Instructions to use Kicel/sparse_imdb_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Kicel/sparse_imdb_classifier with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("FacebookAI/xlm-roberta-base") model = PeftModel.from_pretrained(base_model, "Kicel/sparse_imdb_classifier") - Transformers
How to use Kicel/sparse_imdb_classifier with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Kicel/sparse_imdb_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 676a2f778bf136af63e952e1fbc70586f49627ae8fb0bf7558d3d169a79f2774
- Size of remote file:
- 2.47 MB
- SHA256:
- 86643e0b496d3877d6994d0690c6ef44f70ac680e8d273cfc8344aeaea68d78f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.