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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 38da8faedd8ced6e849e8ee8384e5104eea99841a485559ea27345d600213fb5
- Size of remote file:
- 241 kB
- SHA256:
- 2596f9114d8991bcd02d4729a616f1cc9de4c8f8ed65bbd4157c804ce358e211
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