Instructions to use junzai/bert_finetuning_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use junzai/bert_finetuning_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="junzai/bert_finetuning_test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("junzai/bert_finetuning_test") model = AutoModelForSequenceClassification.from_pretrained("junzai/bert_finetuning_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from junzai/bert_finetuning_test: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/junzai/bert_finetuning_test/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://junzai/bert_finetuning_test/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/junzai/bert_finetuning_test/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- a83ee754d69d56c8e1f98e61ca6fb2baea3b2c10e12ba54832dda8878e592d06
- Size of remote file:
- 438 MB
- SHA256:
- 88176bbade2457864aa24212167d8669935db01fd0a9ecd18d6eed89d2af075a
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