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 training_args.bin from ghadeermobasher/BC4_Modified-scibert_scivocab_uncased: direct link, hf CLI and curl.
- Browser
- Download file 2.86 kB
-
https://huggingface.co/ghadeermobasher/BC4_Modified-scibert_scivocab_uncased/resolve/main/training_args.bin
- Command line
-
hf download hf://ghadeermobasher/BC4_Modified-scibert_scivocab_uncased/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ghadeermobasher/BC4_Modified-scibert_scivocab_uncased/resolve/main/training_args.bin
2.86 kB
- Xet hash:
- 71d5177622942ee22bc4a6529855bbaeece6c1008c8868bb1f7c543a347ffa39
- Size of remote file:
- 2.86 kB
- SHA256:
- 2aa068fd9591f551b300557cb3b909988703602f87e237eb871f2089b027c157
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