Text Classification
Transformers
TensorFlow
distilbert
generated_from_keras_callback
text-embeddings-inference
Instructions to use Docty/imdb_text_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Docty/imdb_text_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Docty/imdb_text_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Docty/imdb_text_model") model = AutoModelForSequenceClassification.from_pretrained("Docty/imdb_text_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from Docty/imdb_text_model: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/Docty/imdb_text_model/resolve/main/tf_model.h5
- Command line
-
hf download hf://Docty/imdb_text_model/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/Docty/imdb_text_model/resolve/main/tf_model.h5
268 MB
- Xet hash:
- ab177c4bd07aa4cacec473f64045e6f102c37edb99ffc80b676560cad04f7edb
- Size of remote file:
- 268 MB
- SHA256:
- 4e32f47c88c1c51a6755049951412a3f624dcfa01da88333cda2526834fa7974
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