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 pytorch_model.bin from CoReProg/IntSemAge: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/CoReProg/IntSemAge/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://CoReProg/IntSemAge@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/CoReProg/IntSemAge/resolve/refs%2Fpr%2F1/pytorch_model.bin
438 MB
- Xet hash:
- 7780fd86c610e1ad51cb574467632fa7979d73eda253ec1fe63f819071bc3031
- Size of remote file:
- 438 MB
- SHA256:
- 8299df0bb7c867fa74a1ee084f64ffad86a1a9974c5560df316dba59fdafa7a8
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