Instructions to use greatakela/bert-base-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use greatakela/bert-base-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="greatakela/bert-base-cased")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("greatakela/bert-base-cased") model = AutoModelForTokenClassification.from_pretrained("greatakela/bert-base-cased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from greatakela/bert-base-cased: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/greatakela/bert-base-cased/resolve/main/training_args.bin
- Command line
-
hf download hf://greatakela/bert-base-cased/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/greatakela/bert-base-cased/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- afda755ed1b321e3417db657804988a607744d5781e47ab3f652e2df9183c69c
- Size of remote file:
- 4.54 kB
- SHA256:
- 1e651eac9e232655c9531090951c1b460f7ab61ddb8b5b37c717508719f74535
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