Instructions to use gaetangate/bart-large_genrl_simpleq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gaetangate/bart-large_genrl_simpleq with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("gaetangate/bart-large_genrl_simpleq") model = AutoModelForSeq2SeqLM.from_pretrained("gaetangate/bart-large_genrl_simpleq", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download train_results.json from gaetangate/bart-large_genrl_simpleq: direct link, hf CLI and curl.
- Browser
- Download file 121 Bytes
-
https://huggingface.co/gaetangate/bart-large_genrl_simpleq/resolve/main/train_results.json
- Command line
-
hf download hf://gaetangate/bart-large_genrl_simpleq/train_results.json
-
curl -L -o train_results.json https://huggingface.co/gaetangate/bart-large_genrl_simpleq/resolve/main/train_results.json
121 Bytes
| { | |
| "epoch": 10.0, | |
| "train_runtime": 28299.6455, | |
| "train_samples": 19235, | |
| "train_samples_per_second": 1.699 | |
| } |