Instructions to use hf-tiny-model-private/tiny-random-Data2VecTextModel 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-Data2VecTextModel 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-Data2VecTextModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-Data2VecTextModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-Data2VecTextModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f202549709509c6cab77ec1d17d5e8831db05bfb544edf529d363cebc35b2d3f
- Size of remote file:
- 352 kB
- SHA256:
- c554d3a17d85d17f8fac8c55fb7796300a94268989baf0b1233190b40899a743
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