Instructions to use diarsabri/LaDPR-context-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use diarsabri/LaDPR-context-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="diarsabri/LaDPR-context-encoder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("diarsabri/LaDPR-context-encoder") model = AutoModel.from_pretrained("diarsabri/LaDPR-context-encoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6faa90de3376fbb7e145a1c0e103f280b31c51653f646897750801eaba33e6f6
- Size of remote file:
- 1.88 GB
- SHA256:
- 0c2ea2f4a0f5f24e70f726411dc628cbe4d63dfcdb39915c733fbd5deee1fcb2
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