Instructions to use aajrami/bert-rand-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aajrami/bert-rand-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="aajrami/bert-rand-small")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("aajrami/bert-rand-small") model = AutoModel.from_pretrained("aajrami/bert-rand-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e734a0f3b1c581062854229c713ab2cb8f0ca71573d3c84e9e03a07692ffd2f5
- Size of remote file:
- 156 MB
- SHA256:
- 254feb60f875f87d4e570c9436e8b3ef4e9eff21da2f725d39876b17ddcddd98
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