Text Classification
Transformers
PyTorch
ONNX
Safetensors
English
distilbert
neural-search
neural-search-query-classification
text-embeddings-inference
Instructions to use ilert/SoQbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ilert/SoQbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ilert/SoQbert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ilert/SoQbert") model = AutoModelForSequenceClassification.from_pretrained("ilert/SoQbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ilert/SoQbert: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/ilert/SoQbert/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ilert/SoQbert/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ilert/SoQbert/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 7f884f4e6937606dcd723282189f7d87d06a397bc0f7989202ce9f9d63d73cd0
- Size of remote file:
- 268 MB
- SHA256:
- 16486f12efcf2c1b9757d8d0cdc4865534c9dc22edd31e79fe7bc76a5ab7893d
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