Instructions to use hf-internal-testing/tiny-random-EsmModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-EsmModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-EsmModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-EsmModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-EsmModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- afa6ba7e7435150fc630c30f9df9f12dd43ba9ccb2903490eca2ecf942b356c4
- Size of remote file:
- 330 kB
- SHA256:
- 372fb93432e72269cbe1949ce6887feab84c11a5503c86f1033e77770dcac009
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