Instructions to use Farjfar/BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Farjfar/BERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Farjfar/BERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Farjfar/BERT") model = AutoModelForTokenClassification.from_pretrained("Farjfar/BERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Farjfar/BERT: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/Farjfar/BERT/resolve/main/training_args.bin
- Command line
-
hf download hf://Farjfar/BERT/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Farjfar/BERT/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- 3f1644cd66fc2713cd86b11ea780bbfeada2efe4af1edd9bc84e46e18d371b79
- Size of remote file:
- 4.98 kB
- SHA256:
- 76b4de6125c4f959a9890a1df9c9a2bc9f238f561d95fe58ae099d4bd3058b49
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