Transformers
Safetensors
Indonesian
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use apwic/summarization-base-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apwic/summarization-base-3 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("apwic/summarization-base-3") model = AutoModelForSeq2SeqLM.from_pretrained("apwic/summarization-base-3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download predict_results.json from apwic/summarization-base-3: direct link, hf CLI and curl.
- Browser
- Download file 332 Bytes
-
https://huggingface.co/apwic/summarization-base-3/resolve/main/predict_results.json
- Command line
-
hf download hf://apwic/summarization-base-3/predict_results.json
-
curl -L -o predict_results.json https://huggingface.co/apwic/summarization-base-3/resolve/main/predict_results.json
332 Bytes
| { | |
| "predict_gen_len": 1.0, | |
| "predict_loss": 0.735045850276947, | |
| "predict_rouge1": 0.4235, | |
| "predict_rouge2": 0.0, | |
| "predict_rougeL": 0.4232, | |
| "predict_rougeLsum": 0.4234, | |
| "predict_runtime": 2255.8566, | |
| "predict_samples": 3752, | |
| "predict_samples_per_second": 1.663, | |
| "predict_steps_per_second": 0.052 | |
| } |