Instructions to use SIRIS-Lab/SciLake-Neuroscience-GLiNER-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SIRIS-Lab/SciLake-Neuroscience-GLiNER-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="SIRIS-Lab/SciLake-Neuroscience-GLiNER-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SIRIS-Lab/SciLake-Neuroscience-GLiNER-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SIRIS-Lab/SciLake-Neuroscience-GLiNER-large: direct link, hf CLI and curl.
- Browser
- Download file 1.84 GB
-
https://huggingface.co/SIRIS-Lab/SciLake-Neuroscience-GLiNER-large/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SIRIS-Lab/SciLake-Neuroscience-GLiNER-large/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SIRIS-Lab/SciLake-Neuroscience-GLiNER-large/resolve/main/pytorch_model.bin
1.84 GB
- Xet hash:
- 73a7916778364fc99dc4666fe48576bf88de1d19911da54ba7f70b1c48c0be0a
- Size of remote file:
- 1.84 GB
- SHA256:
- 1220f8092757d84f908b8283a397769fcc15ad84732dd8d71c611b79df9d163e
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