Instructions to use ghadeermobasher/BC4_Modified-scibert_scivocab_uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ghadeermobasher/BC4_Modified-scibert_scivocab_uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ghadeermobasher/BC4_Modified-scibert_scivocab_uncased")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ghadeermobasher/BC4_Modified-scibert_scivocab_uncased") model = AutoModelForTokenClassification.from_pretrained("ghadeermobasher/BC4_Modified-scibert_scivocab_uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ghadeermobasher/BC4_Modified-scibert_scivocab_uncased: direct link, hf CLI and curl.
- Browser
- Download file 437 MB
-
https://huggingface.co/ghadeermobasher/BC4_Modified-scibert_scivocab_uncased/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ghadeermobasher/BC4_Modified-scibert_scivocab_uncased/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/ghadeermobasher/BC4_Modified-scibert_scivocab_uncased/resolve/main/pytorch_model.bin
437 MB
- Xet hash:
- b47ba52b72bd0d0e86f3c39b8f46dcae4486589cc346f500f6a178c566b65502
- Size of remote file:
- 437 MB
- SHA256:
- b23f546dccd0dc4adfe8e34aabf90442ac10ebbfb541ae4eb54b4617cdf6e073
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