Instructions to use amarshiv86/sentiment-analysis-imdb-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amarshiv86/sentiment-analysis-imdb-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="amarshiv86/sentiment-analysis-imdb-model")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("amarshiv86/sentiment-analysis-imdb-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8f4d6350d7906f44cc95d06570eb264f8a8bc7ac03e4790e0c6c8cdc382e8c97
- Size of remote file:
- 4.79 kB
- SHA256:
- dbc7117ec31a01ab2accaaa6b7c324850d072766bb24989fdc269ccccc0b262c
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