Instructions to use dell-research-harvard/byline-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dell-research-harvard/byline-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dell-research-harvard/byline-detection")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dell-research-harvard/byline-detection") model = AutoModelForTokenClassification.from_pretrained("dell-research-harvard/byline-detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from dell-research-harvard/byline-detection: direct link, hf CLI and curl.
- Browser
- Download file 261 MB
-
https://huggingface.co/dell-research-harvard/byline-detection/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dell-research-harvard/byline-detection/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dell-research-harvard/byline-detection/resolve/main/pytorch_model.bin
261 MB
- Xet hash:
- 2ab811212c74911b66535d7c4ecb57c9dd15a5ccbe2ca2ece39d588280dee605
- Size of remote file:
- 261 MB
- SHA256:
- bdff4ee7e595510b2c0aaf5d63c5a0685ef44675cce0e5df54472c3598099091
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