Instructions to use Reza-Madani/bert-for-sentence-identification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Reza-Madani/bert-for-sentence-identification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Reza-Madani/bert-for-sentence-identification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Reza-Madani/bert-for-sentence-identification") model = AutoModelForSequenceClassification.from_pretrained("Reza-Madani/bert-for-sentence-identification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Reza-Madani/bert-for-sentence-identification: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/Reza-Madani/bert-for-sentence-identification/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Reza-Madani/bert-for-sentence-identification/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Reza-Madani/bert-for-sentence-identification/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 509617e9bc5fe558a17dcae08a4c5442d4c5f1c840fc67bc20a96f0d256d1901
- Size of remote file:
- 438 MB
- SHA256:
- ccdf7c9be110463e63bb4adb94106e2d3cf3fa1b7c67a1563a4b9eb8c311c8e6
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