Instructions to use chano12/update_llama with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use chano12/update_llama with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3.1-8B-Instruct") model = PeftModel.from_pretrained(base_model, "chano12/update_llama") - Notebooks
- Google Colab
- Kaggle
Improve model card for SHARE: Shared Memory-Aware Open-Domain Long-Term Dialogue Model
#1
by nielsr HF Staff - opened
This PR significantly enhances the model card for the SHARE model by populating it with detailed information from the associated paper, "SHARE: Shared Memory-Aware Open-Domain Long-Term Dialogue Dataset Constructed from Movie Script".
Key improvements include:
- A comprehensive model description, outlining its purpose and methodology.
- Links to the official paper (
https://huggingface.co/papers/2410.20682) and the accompanying GitHub repository (https://github.com/share-dialogue/SHARE), providing users with direct access to research and code. - A practical sample usage code snippet demonstrating how to load and use this PEFT adapter model with its
meta-llama/Meta-Llama-3.1-8B-Instructbase model. - Details regarding training data (SHARE dataset) and the EPISODE framework.
- Inclusion of crucial metadata tags for better discoverability on the Hub, such as:
pipeline_tag: text-generationlicense: cc-by-4.0datasets: - SHAREtags: - long-form-dialogue - dialogue-generation
This update aims to provide a clear and informative resource for researchers and developers interested in long-term dialogue systems leveraging shared memories.