Instructions to use hf-internal-testing/tiny-random-Data2VecTextModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Data2VecTextModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-Data2VecTextModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-Data2VecTextModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-Data2VecTextModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f86eb065f57275ba4dcc874064fccafca0ff397ed60e2829f4719e592354ac23
- Size of remote file:
- 352 kB
- SHA256:
- 13989f74985a267df03177da8c9e17c620b04da4b4832d38982daea3595e265e
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