Instructions to use aicast/bert_finetuning_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aicast/bert_finetuning_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aicast/bert_finetuning_test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aicast/bert_finetuning_test") model = AutoModelForSequenceClassification.from_pretrained("aicast/bert_finetuning_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from aicast/bert_finetuning_test: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/aicast/bert_finetuning_test/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://aicast/bert_finetuning_test/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/aicast/bert_finetuning_test/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- c7da9ef99c75262d89872942174bd2c4c76f06d80d66fc948f5fdb84e78beb4b
- Size of remote file:
- 438 MB
- SHA256:
- bf51e89e3725dbbe3e333cd3bae169edcc41d207563c71684337992acec0142b
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