Instructions to use FiveC/TADA-checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FiveC/TADA-checkpoints with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("FiveC/TADA-checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoints/BartTayFinal-SwitchOut/generation_config.json from FiveC/TADA-checkpoints: direct link, hf CLI and curl.
- Browser
- Download file 161 Bytes
-
https://huggingface.co/FiveC/TADA-checkpoints/resolve/main/checkpoints/BartTayFinal-SwitchOut/generation_config.json
- Command line
-
hf download hf://FiveC/TADA-checkpoints/checkpoints/BartTayFinal-SwitchOut/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/FiveC/TADA-checkpoints/resolve/main/checkpoints/BartTayFinal-SwitchOut/generation_config.json
161 Bytes
| { | |
| "bos_token_id": 0, | |
| "decoder_start_token_id": 2, | |
| "eos_token_id": 2, | |
| "forced_eos_token_id": 2, | |
| "pad_token_id": 1, | |
| "transformers_version": "4.57.3" | |
| } | |