Instructions to use bumblebee-testing/tiny-random-LlamaForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bumblebee-testing/tiny-random-LlamaForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bumblebee-testing/tiny-random-LlamaForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bumblebee-testing/tiny-random-LlamaForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("bumblebee-testing/tiny-random-LlamaForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1935015716c5bc478d5c7884dbfc816837f544a22cb2834ee4caba05ac5ca88a
- Size of remote file:
- 195 kB
- SHA256:
- 13c69f2c7626283f054080410f3da00b9eb29138d3190957ea2e3c4b658b761e
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