Instructions to use hf-internal-testing/tiny-random-FalconModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FalconModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-FalconModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-FalconModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-FalconModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a9d80fd0137b47217c75634ffc798e79a9dd47a74557c76e99107160f807c89
- Size of remote file:
- 232 kB
- SHA256:
- d0d8e43e7fc38cf301fe0f5e0f72cf296dae242fbbacd2f2513c02a6bce99f50
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