Instructions to use eunwoneunwon/EPISODE-extraction_llama3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eunwoneunwon/EPISODE-extraction_llama3 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("eunwoneunwon/EPISODE-extraction_llama3", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Improve Model Card for SHARE LoRA Adapter
#1
by nielsr HF Staff - opened
This PR significantly enhances the model card for the SHARE model by providing comprehensive details derived from its associated paper, "SHARE: Shared Memory-Aware Open-Domain Long-Term Dialogue Dataset Constructed from Movie Script".
Key updates include:
- A detailed model description, clarifying its role as a LoRA adapter for
meta-llama/Meta-Llama-3.1-8B-Instructwithin theEPISODEframework. - Linking to the official Hugging Face paper page: SHARE: Shared Memory-Aware Open-Domain Long-Term Dialogue Dataset Constructed from Movie Script.
- Adding the appropriate
pipeline_tag: feature-extractionto improve discoverability, reflecting its function in managing and extracting shared memories. - Specifying the
base_model,language,datasets, andlicensein the metadata. - Including relevant
tagssuch asdialogue,long-term-dialogue,memory,conversational,llama,llm-adapter, andpeft. - Providing a clear usage example for loading and interacting with the LoRA adapter.
- Populating the Bias, Risks, and Limitations section based on the nature of the training data (movie scripts).
- Adding a BibTeX citation for the paper.
Please review and merge this PR to make the model more informative and usable for the community.