Instructions to use A-Funakoshi/bert-wrime-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use A-Funakoshi/bert-wrime-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="A-Funakoshi/bert-wrime-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("A-Funakoshi/bert-wrime-base") model = AutoModelForSequenceClassification.from_pretrained("A-Funakoshi/bert-wrime-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from A-Funakoshi/bert-wrime-base: direct link, hf CLI and curl.
- Browser
- Download file 443 MB
-
https://huggingface.co/A-Funakoshi/bert-wrime-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://A-Funakoshi/bert-wrime-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/A-Funakoshi/bert-wrime-base/resolve/main/pytorch_model.bin
443 MB
- Xet hash:
- 8303f0a65b1533575e3824f446fd5d9d9ca8664784e25b13bce9c339d9524a34
- Size of remote file:
- 443 MB
- SHA256:
- bcc31eef7269ace955c7c243db26a97edcdf58e42d43d477fd124ff3a9354ac1
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