Text Classification
Transformers
TensorFlow
distilbert
generated_from_keras_callback
text-embeddings-inference
Instructions to use ateffal/question-recognizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ateffal/question-recognizer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ateffal/question-recognizer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ateffal/question-recognizer") model = AutoModelForSequenceClassification.from_pretrained("ateffal/question-recognizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from ateffal/question-recognizer: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/ateffal/question-recognizer/resolve/main/tf_model.h5
- Command line
-
hf download hf://ateffal/question-recognizer/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/ateffal/question-recognizer/resolve/main/tf_model.h5
268 MB
- Xet hash:
- 160544825033d522f231e86842be234502fe3cddf3badc955674ea9dfa8793f9
- Size of remote file:
- 268 MB
- SHA256:
- 0d6d072714337139d861acdfee34e20c70c74c3e7e72080edf27e599682c4066
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