Instructions to use borjagomez/bert_model_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use borjagomez/bert_model_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="borjagomez/bert_model_2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("borjagomez/bert_model_2") model = AutoModelForSequenceClassification.from_pretrained("borjagomez/bert_model_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from borjagomez/bert_model_2: direct link, hf CLI and curl.
- Browser
- Download file 3.31 kB
-
https://huggingface.co/borjagomez/bert_model_2/resolve/main/training_args.bin
- Command line
-
hf download hf://borjagomez/bert_model_2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/borjagomez/bert_model_2/resolve/main/training_args.bin
3.31 kB
- Xet hash:
- b5622f87250fc6df0fa5ee4b5167b58d70b2c4d80bb4ed19735d59923cb6d747
- Size of remote file:
- 3.31 kB
- SHA256:
- 9d1ebf686b3609210b8203ad1f7dd1eecaa66089f8a6753ae332df408131392e
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