Instructions to use hf-tiny-model-private/tiny-random-ConvBertModel 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-ConvBertModel 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-ConvBertModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-ConvBertModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-ConvBertModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e45def9de1380da87cfcfdf9a33cc5a8298b3ac1b372b1948b8c671a642f4ae0
- Size of remote file:
- 5.47 MB
- SHA256:
- ce60f93c28ebd3b8c0fc250db34a48baaa8859aba21c5c6e47452ae2b5135256
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