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:
- a2736f7fe8e37e17a0d8b28a9ba97411d731111fc4b038f4ec1ae0bb9efbf000
- Size of remote file:
- 232 kB
- SHA256:
- 5e1557b66d511180b0563963b725742b63553964655726df94f7425c44fc16e7
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