Instructions to use Swarnava/tmp_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Swarnava/tmp_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Swarnava/tmp_trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Swarnava/tmp_trainer") model = AutoModelForSequenceClassification.from_pretrained("Swarnava/tmp_trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e4aa8d1ea3add8c481d2664c971aac15fc38e047f2205e4ec6bd671174b9bda0
- Size of remote file:
- 4.92 kB
- SHA256:
- cb31bcfefac60c79c62e36f4c69bc9722e98bd9f92087f952961a30220c06893
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