Instructions to use hf-internal-testing/tiny-random-FalconForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FalconForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-FalconForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-FalconForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-FalconForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a79196ad658001728b7bac19651b6b24d899f232bdfc6bff6107fb6c2c1ef6af
- Size of remote file:
- 233 kB
- SHA256:
- 5e3efd8f8f1c1393ec002503d02d324dfc9f3549fe7a38d1f6d000c4fd1753d8
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