Cohee/bart-large-cnn-samsum-ChatGPT-onnx
By Cohee · ↓ 8 · ♥ 1 · Updated 2023-09-12
What's in this repo
This page lists the files in Cohee/bart-large-cnn-samsum-ChatGPT-onnx, including decoder_model.onnx, decoder_model_merged.onnx, decoder_model_merged_quantized.onnx and more.
- 8 ONNX models (.onnx files)
- 19 files, including 8 .onnx, 7 .json, 1 .md, 1 .txt
- Last updated 2023-09-12
ONNX files
| File | Size | Download |
|---|---|---|
| onnx/decoder_model.onnx | — | Download |
| onnx/decoder_model_merged.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_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
Qiliang/bart-large-cnn-samsum-ChatGPT_v3 converted to ONNX and quantized using optimum.
bart-large-cnn-samsum-ChatGPT_v3
This model is a fine-tuned version of philschmid/bart-large-cnn-samsum on an unknown dataset.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.2
Model info
Created: 2023-09-12
Updated: 2023-09-12
View on Hugging Face