Instructions to use dhanishetty/Google_bert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dhanishetty/Google_bert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dhanishetty/Google_bert-base-uncased")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dhanishetty/Google_bert-base-uncased") model = AutoModelForTokenClassification.from_pretrained("dhanishetty/Google_bert-base-uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dhanishetty/Google_bert-base-uncased: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/dhanishetty/Google_bert-base-uncased/resolve/main/training_args.bin
- Command line
-
hf download hf://dhanishetty/Google_bert-base-uncased/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dhanishetty/Google_bert-base-uncased/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 8bcc052d1746c63b49c6d039141a9d5373e8d58d00181a992e96b37d6c3daaee
- Size of remote file:
- 5.11 kB
- SHA256:
- 1e65be79e61a6d700406132550d6d41d9406e83c680954dba6996cc9a865c91a
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