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:
- 8e3595eb45adf7c2fca36a2fd29d296ce8f2c3ceaed54087dcfe86874af05417
- Size of remote file:
- 232 kB
- SHA256:
- 8fad870da686b12b4d341c2c4327fc9f7a16cb81198f062386cb8cb2ca5d4409
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