Instructions to use chenqian/bert_finetuning_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chenqian/bert_finetuning_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="chenqian/bert_finetuning_test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("chenqian/bert_finetuning_test") model = AutoModelForSequenceClassification.from_pretrained("chenqian/bert_finetuning_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from chenqian/bert_finetuning_test: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/chenqian/bert_finetuning_test/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://chenqian/bert_finetuning_test/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/chenqian/bert_finetuning_test/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- f86c5890bb0728c799ab145b022e3feed95602d50a654f263c4d88ff4d6cc1ba
- Size of remote file:
- 438 MB
- SHA256:
- 2d9595203e3d2a4b46aa67fdecf814ebee886537e6bf10ccf685b40c595865db
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