Instructions to use zqf03118/bert_finetuning_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zqf03118/bert_finetuning_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="zqf03118/bert_finetuning_test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("zqf03118/bert_finetuning_test") model = AutoModelForMaskedLM.from_pretrained("zqf03118/bert_finetuning_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from zqf03118/bert_finetuning_test: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/zqf03118/bert_finetuning_test/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://zqf03118/bert_finetuning_test/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/zqf03118/bert_finetuning_test/resolve/main/flax_model.msgpack
438 MB
- Xet hash:
- d306915027cdeaae26a6f45685d4a4c51104679709fff2c2ee8df2d85e74a1a0
- Size of remote file:
- 438 MB
- SHA256:
- a6241a3cf092bff25c1f92020856d466ad7f7613f11e331b684261d6f9ae88b9
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