Instructions to use Mithil/Bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mithil/Bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mithil/Bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mithil/Bert") model = AutoModelForSequenceClassification.from_pretrained("Mithil/Bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 897bedc7a2a986384b01e42d52bd6979d202fcedcfc965ed1fba1a4cc4e8758d
- Size of remote file:
- 438 MB
- SHA256:
- b4d3b944ce8a6140522f7042312593d7218e3e0a0e6fab54c0f71e207c659708
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