Instructions to use ghadeermobasher/WLT-BioBERT-Linnaeus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ghadeermobasher/WLT-BioBERT-Linnaeus with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ghadeermobasher/WLT-BioBERT-Linnaeus")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ghadeermobasher/WLT-BioBERT-Linnaeus") model = AutoModelForTokenClassification.from_pretrained("ghadeermobasher/WLT-BioBERT-Linnaeus", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ghadeermobasher/WLT-BioBERT-Linnaeus: direct link, hf CLI and curl.
- Browser
- Download file 2.86 kB
-
https://huggingface.co/ghadeermobasher/WLT-BioBERT-Linnaeus/resolve/main/training_args.bin
- Command line
-
hf download hf://ghadeermobasher/WLT-BioBERT-Linnaeus/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ghadeermobasher/WLT-BioBERT-Linnaeus/resolve/main/training_args.bin
2.86 kB
- Xet hash:
- 5ac4de570464a18b4b1b537db5b22f43b65d377ef312ab346777d1cf4772909a
- Size of remote file:
- 2.86 kB
- SHA256:
- 53b41347660637902910974e32ac59928c8e5e67a52e408f8dc90d56bcaffde5
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