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 training_args.bin from ghadeermobasher/BioNLP13CG-Original-scibert_latest: direct link, hf CLI and curl.
- Browser
- Download file 2.86 kB
-
https://huggingface.co/ghadeermobasher/BioNLP13CG-Original-scibert_latest/resolve/main/training_args.bin
- Command line
-
hf download hf://ghadeermobasher/BioNLP13CG-Original-scibert_latest/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ghadeermobasher/BioNLP13CG-Original-scibert_latest/resolve/main/training_args.bin
2.86 kB
- Xet hash:
- ec19c4b1941097a886041d231c343a6389da8b4a9d793bdc4aedccebbe82797f
- Size of remote file:
- 2.86 kB
- SHA256:
- 7c13693d03e4b7c0b4aeae27b8d99519e57af47e65c70a488052f3230d6df043
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