Instructions to use uvegesistvan/optimized_proposal_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uvegesistvan/optimized_proposal_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="uvegesistvan/optimized_proposal_1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("uvegesistvan/optimized_proposal_1") model = AutoModelForSequenceClassification.from_pretrained("uvegesistvan/optimized_proposal_1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f48ccdf8dddb979f4e8a9637c59c4be66a02b5319e95e2962ddbd75f55a059af
- Size of remote file:
- 5.24 kB
- SHA256:
- 4b5c8cbd5da632b32e03f38255da1b60850a45befb04284808b91121020c0053
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