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/tokenizer_config.json from ilert/SoQbert: direct link, hf CLI and curl.
- Browser
- Download file 1.25 kB
-
https://huggingface.co/ilert/SoQbert/resolve/main/onnx/tokenizer_config.json
- Command line
-
hf download hf://ilert/SoQbert/onnx/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/ilert/SoQbert/resolve/main/onnx/tokenizer_config.json
1.25 kB
- Xet hash:
- 44724acf230b28592107ad465f26c7969ad9dfb4128d96d6af981e522f4a706c
- Size of remote file:
- 1.25 kB
- SHA256:
- 9df5a6bb4f12d30d81f8043c57b4714a8ef69ed19921531187dfb3c4fb724ac0
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