Instructions to use RogerKam/BERT-large2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RogerKam/BERT-large2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RogerKam/BERT-large2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RogerKam/BERT-large2") model = AutoModelForSequenceClassification.from_pretrained("RogerKam/BERT-large2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from RogerKam/BERT-large2: direct link, hf CLI and curl.
- Browser
- Download file 4.6 kB
-
https://huggingface.co/RogerKam/BERT-large2/resolve/main/training_args.bin
- Command line
-
hf download hf://RogerKam/BERT-large2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/RogerKam/BERT-large2/resolve/main/training_args.bin
4.6 kB
- Xet hash:
- 22aa9264c853d40df15dfb3a802ab62f531d261ede6ba5020ecf153fad0643d9
- Size of remote file:
- 4.6 kB
- SHA256:
- 71dbb2765c5f5e86f6b0cbe3e1ac35bab10fac368a6aa3e4e12aa06930946892
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