This checkpoint should be loaded into BartForConditionalGeneration.frompretrained. See the BART docs for more information.
Open-weight model · Summarization
t5-base-indonesian-summarization-cased
by Cahya Wirawan cahya/t5-base-indonesian-summarization-cased
Finetuned T5 base summarization model for Indonesian. t5-base-indonesian-summarization-cased model is based on t5-base-bahasa-summarization-cased by huseinzol05, finetuned using idliputan6 dataset.
Parameters—
Context—
Weights2.9 GB
License—
AccessOpen weights
Monthly Downloads11k
Model Card
Finetuned T5 base summarization model for Indonesian. t5-base-indonesian-summarization-cased model is based on t5-base-bahasa-summarization-cased by huseinzol05, finetuned using idliputan6 dataset.
Excerpt from the card by Cahya Wirawan.
Configuration
- Architecture
- T5ForConditionalGeneration
- Vocabulary size
- 32,128
- Model type
- t5
Identity and Version
- Repository
- cahya/t5-base-indonesian-summarization-cased
- Publisher
- Cahya Wirawan
- Task
- Summarization
- Modality
- Text
- Library
- transformers
- Parameters
- Not stated by the source
- Languages
- id
- Revision
- 6db5daf9f208e77e56de7303a373d93cef771aed
- First published
- 2022-03-02
- Last updated
- 2022-11-19
Files and Weights
9 files, 2.9 GB in total. The weights are 3 files totalling 2.9 GB in bin, h5, msgpack.
Weights3 files · 2.9 GB
Configuration2 files · 2.4 KB
Tokenizer2 files · 795.1 KB
Documentation1 file · 1.7 KB
Repository1 file · 437 B
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| flax_model.msgpack | Weights | 891.6 MB | fb1896579cbe |
| pytorch_model.bin | Weights | 891.7 MB | 876920295431 |
| tf_model.h5 | Weights | 1.1 GB | 993562bf0249 |
| config.json | Configuration | 657 B | — |
| special_tokens_map.json | Configuration | 1.8 KB | — |
| README.md | Documentation | 1.7 KB | — |
| .gitattributes | Repository | 437 B | — |
| spiece.model | Tokenizer | 793.0 KB | — |
| tokenizer_config.json | Tokenizer | 2.1 KB | — |
License and Download
- License
- Not stated by the source
- Access
- Open weights, no gate
- Download size
- 2.9 GB
Download from Cahya Wirawan
Released by Cahya Wirawan through its official repository on Hugging Face.
Built From
- Trained on (disclosed) id_liputan6
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 2.9 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
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This model was trained using Amazon SageMaker and the new Hugging Face Deep Learning container.
This checkpoint should be loaded into BartForConditionalGeneration.frompretrained. See the BART docs for more information.
This repository contains the mT5 checkpoint finetuned on the 45 languages of XL-Sum dataset. For finetuning details and scripts, see the paper and the official repository. Scores on the XL-Sum test sets are as follows: Language | ROUGE-1 / ROUGE-2 / ROUGE-L Amharic | 20.0485 / 7.4111 / 18.0753 Arabic | 34.9107 / 14.7937 / 29.1623 Azerbaijani | 21.4227 / 9.5214 / 19.3331 Bengali | 29.5653 / 12.1095 / 25.1315 Burmese | 15.9626 / 5.1477 / 14.1819 Chinese (Simplified) | 39.4071 / 17.7913 / 33.406 Chinese (Traditional) | 37.1866 / 17.1432 / 31.6184 English | 37.601 / 15.1536 / 29.8817 French | 35.3398 / 16.1739 / 28.2041 Gujarati | 21.9619 / 7.7417 / 19.86 Hausa | 39.4375 / 17.6786 / 31.6667…