tryolabs/long-t5-tglobal-base-blogpost-cqa-onnx
By tryolabs · ↓ 6 · ♥ 8 · Updated 2023-01-03
What's in this repo
This page lists the files in tryolabs/long-t5-tglobal-base-blogpost-cqa-onnx, including decoder_model.onnx, decoder_with_past_model.onnx, encoder_model.onnx.
- 3 ONNX models (.onnx files)
- 12 files, including 5 .json, 3 .onnx, 1 .md, 1 .py, 1 .model
- Last updated 2023-01-03
ONNX files
| File | Size | Download |
|---|---|---|
| decoder_model.onnx | — | Download |
| decoder_with_past_model.onnx | — | Download |
| encoder_model.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
Fine-tuned LongT5 for Conversational QA (ONNX Format)
This model is an ONNX export of tryolabs/long-t5-tglobal-base-blogpost-cqa, a fine-tuned version of long-t5-tglobal-base for the task of Conversational QA. The model was fine-tuned on the SQuADv2 and CoQA datasets and on Tryolabs' own custom dataset, TryoCoQA.
The model was exported using 🤗 Optimum's exporters feature, which separates the original model into three componentes: the encoder, the decoder with the Language Modeling head, and the decoder with hidden states as additional inputs. Using 🤗 Optimum and ONNX Runtime, you can combine these components for faster inference.
You can find the details on how we fine-tuned the model and built TryoCoQA on our blog post!
You can also play with the model on the following space.
Results
- Fine-tuning for 3 epochs on SQuADv2 and CoQA combined achieved a 74.29 F1 score on the test set.
- Fine-tuning for 166 epochs on TryoCoQA achieved a 54.77 F1 score on the test set.
Model info
Created: 2022-12-20
Updated: 2023-01-03
View on Hugging FaceFiles (12)
Related models
More from tryolabs
More models
No task type declared.