Instructions to use dejanai/LinkBERT-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dejanai/LinkBERT-mini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dejanai/LinkBERT-mini")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("dejanai/LinkBERT-mini") model = AutoModelForMaskedLM.from_pretrained("dejanai/LinkBERT-mini", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from dejanai/LinkBERT-mini: direct link, hf CLI and curl.
- Browser
- Download file 44.4 MB
-
https://huggingface.co/dejanai/LinkBERT-mini/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dejanai/LinkBERT-mini/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dejanai/LinkBERT-mini/resolve/main/pytorch_model.bin
44.4 MB
- Xet hash:
- 04cb925e931a7bbda51aca3f380b0ffc7fb031c03ab5ce6b7eefa7b0c32432da
- Size of remote file:
- 44.4 MB
- SHA256:
- 5b4adc44b39b4de3ef227254862396551d0860b6aedd80b03a361fe0717bbcfd
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