Instructions to use pkushiqiang/bert-split-title-org with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pkushiqiang/bert-split-title-org with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="pkushiqiang/bert-split-title-org")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("pkushiqiang/bert-split-title-org") model = AutoModelForTokenClassification.from_pretrained("pkushiqiang/bert-split-title-org", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from pkushiqiang/bert-split-title-org: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/pkushiqiang/bert-split-title-org/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://pkushiqiang/bert-split-title-org/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/pkushiqiang/bert-split-title-org/resolve/main/pytorch_model.bin
431 MB
- Xet hash:
- ecd583ad77f301246bf1f783eb1e7fcae940316dcedfed99ffeb2bee748f1b52
- Size of remote file:
- 431 MB
- SHA256:
- baf8541d14f3e713ef16d652df028a6328518fcc79623884cd4406a8105ee1ee
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