Text Classification
Transformers
TensorFlow
distilbert
generated_from_keras_callback
text-embeddings-inference
Instructions to use TirkNork/text_classification_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TirkNork/text_classification_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TirkNork/text_classification_test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TirkNork/text_classification_test") model = AutoModelForSequenceClassification.from_pretrained("TirkNork/text_classification_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from TirkNork/text_classification_test: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/TirkNork/text_classification_test/resolve/main/tf_model.h5
- Command line
-
hf download hf://TirkNork/text_classification_test/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/TirkNork/text_classification_test/resolve/main/tf_model.h5
268 MB
- Xet hash:
- b3c8c005072de8d4adb2b02204858cd22f169bbb5ceadb33032508118a3b69a8
- Size of remote file:
- 268 MB
- SHA256:
- ba9d2a908e7ee9b0cf56544b9cfc8b871b5622aa3184d483072560b90f4002fd
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