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 pytorch_model.bin from ghadeermobasher/WLT-BioBERT-Linnaeus: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/ghadeermobasher/WLT-BioBERT-Linnaeus/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ghadeermobasher/WLT-BioBERT-Linnaeus/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ghadeermobasher/WLT-BioBERT-Linnaeus/resolve/main/pytorch_model.bin
431 MB
- Xet hash:
- 9702f1a33c8a09caab9176fc17da9f798070a2ccb4e5b3a9f5bf19e5280137f4
- Size of remote file:
- 431 MB
- SHA256:
- 1d925619cb22a4ca255921b4db7c8b7360892d3b3896e923719b49770127d8c1
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