Instructions to use Arro94/nova-model-benchmark with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Arro94/nova-model-benchmark with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Arro94/nova-model-benchmark")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Arro94/nova-model-benchmark") model = AutoModelForSequenceClassification.from_pretrained("Arro94/nova-model-benchmark", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Arro94/nova-model-benchmark: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/Arro94/nova-model-benchmark/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Arro94/nova-model-benchmark/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Arro94/nova-model-benchmark/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 7d799e4ee58792ef4b373cf0f3e561d7c764514fb693a3b7d6ebc2aaa752f10c
- Size of remote file:
- 499 MB
- SHA256:
- 13e1edfd958609a79b52f324ea23230adbd544b53504792ec07e28c7a3c38364
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