Instructions to use EshAhm/Paper-Matcher-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EshAhm/Paper-Matcher-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="EshAhm/Paper-Matcher-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("EshAhm/Paper-Matcher-bert") model = AutoModelForSequenceClassification.from_pretrained("EshAhm/Paper-Matcher-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from EshAhm/Paper-Matcher-bert: direct link, hf CLI and curl.
- Browser
- Download file 5.27 kB
-
https://huggingface.co/EshAhm/Paper-Matcher-bert/resolve/main/training_args.bin
- Command line
-
hf download hf://EshAhm/Paper-Matcher-bert/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/EshAhm/Paper-Matcher-bert/resolve/main/training_args.bin
5.27 kB
- Xet hash:
- db476e7499a70456b152cdcf99bcf23465108823ccd9c2a2858191dc22ec7db8
- Size of remote file:
- 5.27 kB
- SHA256:
- 9e6be198631623953cfba712d0add58731b30ccf129dddd6fcad2da2a1c235e6
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