Instructions to use research-backup/mt5-base-frquad-qg-trimmed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use research-backup/mt5-base-frquad-qg-trimmed with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("research-backup/mt5-base-frquad-qg-trimmed") model = AutoModelForSeq2SeqLM.from_pretrained("research-backup/mt5-base-frquad-qg-trimmed") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Vocabulary Trimmed lmqg/mt5-base-frquad-qg: vocabtrimmer/mt5-base-frquad-qg-trimmed
This model is a trimmed version of lmqg/mt5-base-frquad-qg by vocabtrimmer, a tool for trimming vocabulary of language models to compress the model size.
Following table shows a summary of the trimming process.
| lmqg/mt5-base-frquad-qg | vocabtrimmer/mt5-base-frquad-qg-trimmed | |
|---|---|---|
| parameter_size_full | 582,384,384 | 399,578,880 |
| parameter_size_embedding | 384,155,136 | 201,349,632 |
| vocab_size | 250,101 | 131,087 |
| compression_rate_full | 100.0 | 68.61 |
| compression_rate_embedding | 100.0 | 52.41 |
Following table shows the parameter used to trim vocabulary.
| language | dataset | dataset_column | dataset_name | dataset_split | target_vocab_size | min_frequency |
|---|---|---|---|---|---|---|
| fr | vocabtrimmer/mc4_validation | text | fr | validation | 2 |
- Downloads last month
- 4
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support