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 flax_model.msgpack from junzai/bert_finetuning_test: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/junzai/bert_finetuning_test/resolve/refs%2Fpr%2F1/flax_model.msgpack
- Command line
-
hf download hf://junzai/bert_finetuning_test@refs/pr/1/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/junzai/bert_finetuning_test/resolve/refs%2Fpr%2F1/flax_model.msgpack
438 MB
- Xet hash:
- f89a9e9ec431134ae5e6d24e8c56204728499b56e1ef4ae46b89116b1617e738
- Size of remote file:
- 438 MB
- SHA256:
- 8405947f0be54b19d8cd26b75ed3020a66ac2b665123c4397c149b4e02a5d551
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