Instructions to use MENG21/results_bert-large-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MENG21/results_bert-large-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MENG21/results_bert-large-uncased")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MENG21/results_bert-large-uncased") model = AutoModelForSequenceClassification.from_pretrained("MENG21/results_bert-large-uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from MENG21/results_bert-large-uncased: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/MENG21/results_bert-large-uncased/resolve/main/training_args.bin
- Command line
-
hf download hf://MENG21/results_bert-large-uncased/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/MENG21/results_bert-large-uncased/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- 18ca5fde2c2a3e4723d8a143a415253dc9ed0d59a46f0057d95c04a8e5b14f48
- Size of remote file:
- 4.73 kB
- SHA256:
- 7c4c589f8508fbb8530d8e6bf84858139f5b74078ba7d934deb40d417e3bb4d7
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