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 training_args.bin from beverlyjfu/DistilProtBert-finetuned-localization: direct link, hf CLI and curl.
- Browser
- Download file 3.64 kB
-
https://huggingface.co/beverlyjfu/DistilProtBert-finetuned-localization/resolve/main/training_args.bin
- Command line
-
hf download hf://beverlyjfu/DistilProtBert-finetuned-localization/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/beverlyjfu/DistilProtBert-finetuned-localization/resolve/main/training_args.bin
3.64 kB
- Xet hash:
- 8acae0bf70439ce8dc4ac301783d1c92b724e808105c84d460272b4b9f9305bf
- Size of remote file:
- 3.64 kB
- SHA256:
- 252389b34c9d127ed9d7169d7e8ae49d7322d5fa6bd7d0a27d190e8c4707dde0
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