Instructions to use LilRg/ECE-1B-FineTuning-PRYMMAL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use LilRg/ECE-1B-FineTuning-PRYMMAL with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("<base-model-id>") model.load_adapter("LilRg/ECE-1B-FineTuning-PRYMMAL", set_active=True) - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from LilRg/ECE-1B-FineTuning-PRYMMAL: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/LilRg/ECE-1B-FineTuning-PRYMMAL/resolve/main/tokenizer.json
- Command line
-
hf download hf://LilRg/ECE-1B-FineTuning-PRYMMAL/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/LilRg/ECE-1B-FineTuning-PRYMMAL/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 0448307de52b767e89b211ae9538ecf7e13d71ae4069712283bde6bfad3e02fb
- Size of remote file:
- 11.4 MB
- SHA256:
- 85acc0ed1a93f8b0e6c803b53edf0fe4898ac19a3fff657f21020d280364a0cf
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