Instructions to use Ekanabasi/formation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use Ekanabasi/formation with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("<base-model-id>") model.load_adapter("Ekanabasi/formation", set_active=True) - Notebooks
- Google Colab
- Kaggle
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Download README.md from Ekanabasi/formation: direct link, hf CLI and curl.
- Browser
- Download file 498 Bytes
-
https://huggingface.co/Ekanabasi/formation/resolve/main/README.md
- Command line
-
hf download hf://Ekanabasi/formation/README.md
-
curl -L -o README.md https://huggingface.co/Ekanabasi/formation/resolve/main/README.md
498 Bytes
metadata
license: apache-2.0
datasets:
- facebook/research-plan-gen
language:
- ab
metrics:
- bertscore
base_model:
- Lightricks/LTX-2
new_version: Lightricks/LTX-2
pipeline_tag: summarization
library_name: adapter-transformers
tags:
- legal
license: apache-2.0 datasets:
- facebook/research-plan-gen language:
- ab metrics:
- bertscore base_model:
- zai-org/GLM-4.7 new_version: zai-org/GLM-4.7 pipeline_tag: token-classification library_name: adapter-transformers tags:
- finance --- formation