Instructions to use hf-tiny-model-private/tiny-random-BloomModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-BloomModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-BloomModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-BloomModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-BloomModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d3ba32041c2656103b7129ceaefbcc1bea3447d3147c1579df3df20328e6bf3f
- Size of remote file:
- 392 kB
- SHA256:
- c367a6897be9bce1935770d064ffa1db565046d86cba52e5bbaa6be73fa27b5e
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