Instructions to use BogdanKuloren/continual-learning-paper-embeddings-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BogdanKuloren/continual-learning-paper-embeddings-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="BogdanKuloren/continual-learning-paper-embeddings-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("BogdanKuloren/continual-learning-paper-embeddings-model") model = AutoModel.from_pretrained("BogdanKuloren/continual-learning-paper-embeddings-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from BogdanKuloren/continual-learning-paper-embeddings-model: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/BogdanKuloren/continual-learning-paper-embeddings-model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://BogdanKuloren/continual-learning-paper-embeddings-model/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/BogdanKuloren/continual-learning-paper-embeddings-model/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 6ec639da5bf51b00bdbe9e09bc829451a7f8da3b03e9ddc1610c06155bb32db2
- Size of remote file:
- 438 MB
- SHA256:
- 234a3847cd7f944604e41190e4cf5ffce056e039469cf1f10637c7b8878b700e
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