Instructions to use Shushant/tmp_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shushant/tmp_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Shushant/tmp_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Shushant/tmp_model") model = AutoModelForSequenceClassification.from_pretrained("Shushant/tmp_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9ab52c59af3014628a24442044bc9a439fc5447f6e4b15a5d0c278c3ca73a98b
- Size of remote file:
- 4.47 kB
- SHA256:
- 26ab84d4d3a8aac97ef59ea47fb5d509e836ec882e1bd92faea90b9cde3977c8
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