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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 88ec6ba4787068827c3b3c78715a4eafe6448c5ef0cbcac12f675798720c01df
- Size of remote file:
- 439 kB
- SHA256:
- 22fae2a1a699a5d9a5700e3f9c39028afc9180cbb660df41bfa312077119e67e
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