Instructions to use askulkarni2/imdber with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use askulkarni2/imdber with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="askulkarni2/imdber")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("askulkarni2/imdber") model = AutoModelForSequenceClassification.from_pretrained("askulkarni2/imdber", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e4f5e5160a8981ad11bbe09d643c35c237346b4ab4c37464ec3184464f844816
- Size of remote file:
- 268 MB
- SHA256:
- e6dd003aff81a59f32fc777b8e5c868e14f42a26f1bb56d42152548e89170bd0
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