Instructions to use hf-internal-testing/tiny-random-BloomModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BloomModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-BloomModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-BloomModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-BloomModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d3116523b40b5a91fb03901556b737832d1e8c79f4e0248c95f4c159e5b3d0b6
- Size of remote file:
- 405 kB
- SHA256:
- a4881b535f6c30394996915d3d2d7b0170eb2e39873361bb74e636d2dc6a24e7
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