Instructions to use tk3879110/bert_cn_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tk3879110/bert_cn_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tk3879110/bert_cn_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tk3879110/bert_cn_finetuning") model = AutoModelForSequenceClassification.from_pretrained("tk3879110/bert_cn_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from tk3879110/bert_cn_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 409 MB
-
https://huggingface.co/tk3879110/bert_cn_finetuning/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://tk3879110/bert_cn_finetuning/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/tk3879110/bert_cn_finetuning/resolve/main/pytorch_model.bin
409 MB
- Xet hash:
- 18912d47a993d2c926a04d075a81a259f639a407f29677ddf01ae3e201d79278
- Size of remote file:
- 409 MB
- SHA256:
- bccb6770bf88f6cd9dda8e8ae7cf51f65b9aae2b92826595f9d2f9e743cf8b4f
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