Instructions to use ghadeermobasher/BioNLP13CG-Original-scibert_latest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ghadeermobasher/BioNLP13CG-Original-scibert_latest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ghadeermobasher/BioNLP13CG-Original-scibert_latest")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ghadeermobasher/BioNLP13CG-Original-scibert_latest") model = AutoModelForTokenClassification.from_pretrained("ghadeermobasher/BioNLP13CG-Original-scibert_latest", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ghadeermobasher/BioNLP13CG-Original-scibert_latest: direct link, hf CLI and curl.
- Browser
- Download file 437 MB
-
https://huggingface.co/ghadeermobasher/BioNLP13CG-Original-scibert_latest/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ghadeermobasher/BioNLP13CG-Original-scibert_latest/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/ghadeermobasher/BioNLP13CG-Original-scibert_latest/resolve/main/pytorch_model.bin
437 MB
- Xet hash:
- 3365897de04fcc9197a4d68b74b5d6e0a51ce51ae359e75e728c2f4775950618
- Size of remote file:
- 437 MB
- SHA256:
- a16cdb1bd13636cee5a9119d9378d2ce6b4f7f19a37f836da13dac8aef6ed88c
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