Instructions to use liangxiaoxiao/bert_finetuning_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use liangxiaoxiao/bert_finetuning_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="liangxiaoxiao/bert_finetuning_test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("liangxiaoxiao/bert_finetuning_test") model = AutoModelForSequenceClassification.from_pretrained("liangxiaoxiao/bert_finetuning_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from liangxiaoxiao/bert_finetuning_test: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/liangxiaoxiao/bert_finetuning_test/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://liangxiaoxiao/bert_finetuning_test/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/liangxiaoxiao/bert_finetuning_test/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- e9ea865732d43f575f56c068b9f058b3229ff9bd150bd6870b463fc7dc828c5b
- Size of remote file:
- 438 MB
- SHA256:
- 5763436eeacae103dc0181b613b63b642d89a4376a458282a1e687a46bc16e29
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