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:
- 5528314520ccd9fccf7ae37400f5113f42f496bd4f604b92c62ac8b4ebafb55b
- Size of remote file:
- 233 kB
- SHA256:
- bb1487c0b2e320a48b1dfc2aa75b9ccd1348685a20d8002322e9dfb25907cb91
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