Instructions to use zharry29/step_benchmark_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zharry29/step_benchmark_bert with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultipleChoice tokenizer = AutoTokenizer.from_pretrained("zharry29/step_benchmark_bert") model = AutoModelForMultipleChoice.from_pretrained("zharry29/step_benchmark_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from zharry29/step_benchmark_bert: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/zharry29/step_benchmark_bert/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://zharry29/step_benchmark_bert/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/zharry29/step_benchmark_bert/resolve/main/flax_model.msgpack
438 MB
- Xet hash:
- 3177118cb8f316d8a6ac9c0fb7d4e56a658a7144366a5b6ea379fda618892358
- Size of remote file:
- 438 MB
- SHA256:
- ca9f660cbcc2cce91983f22d0500c832fc7ea798743236852782c68a6669dfd1
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