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:
- 26c5e71102139743e7ac9d60e935095ca44f0883c5d3d2b184ca205ddafdb31e
- Size of remote file:
- 232 kB
- SHA256:
- a61d160206bf6df3bb86cf30f2b4b9be3f664101e69b2a3ebc624092a9df1e2c
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