Xenova/long-t5-tglobal-base-16384-book-summary
By Xenova · ↓ 15 · ♥ 1 · Updated 2024-10-08
What's in this repo
This page lists the files in Xenova/long-t5-tglobal-base-16384-book-summary, including decoder_model.onnx, decoder_model_merged.onnx, decoder_model_merged_fp16.onnx and more.
- 10 ONNX models (.onnx files)
- 19 files, including 10 .onnx, 6 .json, 1 .md, 1 .model
- Last updated 2024-10-08
ONNX files
| File | Size | Download |
|---|---|---|
| onnx/decoder_model.onnx | — | Download |
| onnx/decoder_model_merged.onnx | — | Download |
| onnx/decoder_model_merged_fp16.onnx | — | Download |
| onnx/decoder_model_merged_quantized.onnx | — | Download |
| onnx/decoder_model_quantized.onnx | — | Download |
| onnx/decoder_with_past_model.onnx | — | Download |
| onnx/decoder_with_past_model_quantized.onnx | — | Download |
| onnx/encoder_model.onnx | — | Download |
| onnx/encoder_model_fp16.onnx | — | Download |
| onnx/encoder_model_quantized.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
https://huggingface.co/pszemraj/long-t5-tglobal-base-16384-book-summary with ONNX weights to be compatible with Transformers.js.
Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using 🤗 Optimum and structuring your repo like this one (with ONNX weights located in a subfolder named onnx).
Model info
Created: 2023-09-18
Updated: 2024-10-08
View on Hugging FaceFiles (19)
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