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 onnx/config.json from ilert/SoQbert: direct link, hf CLI and curl.
- Browser
- Download file 699 Bytes
-
https://huggingface.co/ilert/SoQbert/resolve/main/onnx/config.json
- Command line
-
hf download hf://ilert/SoQbert/onnx/config.json
-
curl -L -o config.json https://huggingface.co/ilert/SoQbert/resolve/main/onnx/config.json
699 Bytes
- Xet hash:
- 805b145236955dca06bbca656905b549328497c5a6fc6dcf879c1b6144fd77aa
- Size of remote file:
- 699 Bytes
- SHA256:
- a77158694022cebef3473253d0daf8c923adb3a6ef41c3ab69c9238adfff3f81
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