Instructions to use naveenVakada/tiny_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use naveenVakada/tiny_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="naveenVakada/tiny_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("naveenVakada/tiny_model") model = AutoModelForSequenceClassification.from_pretrained("naveenVakada/tiny_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4514159e8ab2bbfe11e488950c1f4b75da4dcd8d18fa6768b5f37627ed45701d
- Size of remote file:
- 5.05 kB
- SHA256:
- 605232d456abebd5def995a845264bc23ed652eb9986140bb8d03aee830305e7
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