Transformers
Safetensors
Indonesian
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use apwic/summarization-base-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apwic/summarization-base-2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("apwic/summarization-base-2") model = AutoModelForSeq2SeqLM.from_pretrained("apwic/summarization-base-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download predict_results.json from apwic/summarization-base-2: direct link, hf CLI and curl.
- Browser
- Download file 333 Bytes
-
https://huggingface.co/apwic/summarization-base-2/resolve/main/predict_results.json
- Command line
-
hf download hf://apwic/summarization-base-2/predict_results.json
-
curl -L -o predict_results.json https://huggingface.co/apwic/summarization-base-2/resolve/main/predict_results.json
333 Bytes
| { | |
| "predict_gen_len": 1.0, | |
| "predict_loss": 0.6919664740562439, | |
| "predict_rouge1": 0.4076, | |
| "predict_rouge2": 0.0, | |
| "predict_rougeL": 0.4074, | |
| "predict_rougeLsum": 0.4073, | |
| "predict_runtime": 2530.1936, | |
| "predict_samples": 3737, | |
| "predict_samples_per_second": 1.477, | |
| "predict_steps_per_second": 0.046 | |
| } |