Instructions to use jfkback/hypencoder.8_layer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jfkback/hypencoder.8_layer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="jfkback/hypencoder.8_layer")# pip install -U transformers accelerate # Load model directly from transformers import HypencoderDualEncoder model = HypencoderDualEncoder.from_pretrained("jfkback/hypencoder.8_layer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from jfkback/hypencoder.8_layer: direct link, hf CLI and curl.
- Browser
- Download file 711 kB
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https://huggingface.co/jfkback/hypencoder.8_layer/resolve/main/tokenizer.json
- Command line
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hf download hf://jfkback/hypencoder.8_layer/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/jfkback/hypencoder.8_layer/resolve/main/tokenizer.json
711 kB
File too large to display, you can check the raw version instead.