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:
- 33ada5dd945aea98decd3568baecd31d5182c7fa6f8d5a08fc5794ad8101bc9a
- Size of remote file:
- 268 MB
- SHA256:
- 662278448a7f06d0b6f8568e138a4006aeb6a8476bef8e9278e37780c30bfc1c
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