Instructions to use Connor-tech/bert_cn_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Connor-tech/bert_cn_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Connor-tech/bert_cn_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Connor-tech/bert_cn_finetuning") model = AutoModelForSequenceClassification.from_pretrained("Connor-tech/bert_cn_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Connor-tech/bert_cn_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 1.46 kB
-
https://huggingface.co/Connor-tech/bert_cn_finetuning/resolve/main/training_args.bin
- Command line
-
hf download hf://Connor-tech/bert_cn_finetuning/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/Connor-tech/bert_cn_finetuning/resolve/main/training_args.bin
1.46 kB
- Xet hash:
- 1e61e0bf2fb107d45933af265a120a85d1a05219e9fb2b30c17afed7821a6581
- Size of remote file:
- 1.46 kB
- SHA256:
- fb464c69887e04e4fbc2b048c3691191ee6451599b2aa47b494ddc8ed40cb8f4
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