Text Classification
Transformers
TensorFlow
distilbert
generated_from_keras_callback
text-embeddings-inference
Instructions to use rsaketh02/imdb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rsaketh02/imdb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rsaketh02/imdb")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rsaketh02/imdb") model = AutoModelForSequenceClassification.from_pretrained("rsaketh02/imdb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from rsaketh02/imdb: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/rsaketh02/imdb/resolve/main/tf_model.h5
- Command line
-
hf download hf://rsaketh02/imdb/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/rsaketh02/imdb/resolve/main/tf_model.h5
268 MB
- Xet hash:
- dd648ae90b2dc94d4cb9396696d3f7af8eb3ed89feffbb359cccadd91e4930aa
- Size of remote file:
- 268 MB
- SHA256:
- 4d8682193ffe5eaa50d8c2682ccb561b7b1ca28939834b98eec9d1c23df0389a
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