Instructions to use CoReProg/IntSemAge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CoReProg/IntSemAge with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CoReProg/IntSemAge")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CoReProg/IntSemAge") model = AutoModelForSequenceClassification.from_pretrained("CoReProg/IntSemAge", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from CoReProg/IntSemAge: direct link, hf CLI and curl.
- Browser
- Download file 3.38 kB
-
https://huggingface.co/CoReProg/IntSemAge/resolve/main/training_args.bin
- Command line
-
hf download hf://CoReProg/IntSemAge/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CoReProg/IntSemAge/resolve/main/training_args.bin
3.38 kB
- Xet hash:
- 80d9177b50f7335540404e92939395fa14f242a58af6710b17d784066ce58980
- Size of remote file:
- 3.38 kB
- SHA256:
- 54ad833f91515a593cc09d75e7e16142999c0fb8195bd3ed9e529b34c96e8e34
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