Text Classification
Transformers
TensorFlow
distilbert
generated_from_keras_callback
text-embeddings-inference
Instructions to use jonathanfernandes/imdb_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonathanfernandes/imdb_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jonathanfernandes/imdb_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jonathanfernandes/imdb_model") model = AutoModelForSequenceClassification.from_pretrained("jonathanfernandes/imdb_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from jonathanfernandes/imdb_model: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/jonathanfernandes/imdb_model/resolve/main/tf_model.h5
- Command line
-
hf download hf://jonathanfernandes/imdb_model/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/jonathanfernandes/imdb_model/resolve/main/tf_model.h5
268 MB
- Xet hash:
- 3399bb60929e573ffea40ee595f5a9c42c3779af1e5ce76b478266a08c0fba4c
- Size of remote file:
- 268 MB
- SHA256:
- 007c23ad1748901616d6e995bc898ba3e07642d60354dd2825c4369f37b98b57
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