Instructions to use beverlyjfu/DistilProtBert-finetuned-localization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use beverlyjfu/DistilProtBert-finetuned-localization with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="beverlyjfu/DistilProtBert-finetuned-localization")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("beverlyjfu/DistilProtBert-finetuned-localization") model = AutoModelForSequenceClassification.from_pretrained("beverlyjfu/DistilProtBert-finetuned-localization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from beverlyjfu/DistilProtBert-finetuned-localization: direct link, hf CLI and curl.
- Browser
- Download file 924 MB
-
https://huggingface.co/beverlyjfu/DistilProtBert-finetuned-localization/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://beverlyjfu/DistilProtBert-finetuned-localization/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/beverlyjfu/DistilProtBert-finetuned-localization/resolve/main/pytorch_model.bin
924 MB
- Xet hash:
- 2758986c44eb90951c182f8a69e585f3004752963b34021dac87d9d25098bed6
- Size of remote file:
- 924 MB
- SHA256:
- 6ea569f062af38b7e491ef7d7ff723788f11000290a91bb17c0e611635c05ad2
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