Instructions to use gasolsun/DynamicRAG-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gasolsun/DynamicRAG-8B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="gasolsun/DynamicRAG-8B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("gasolsun/DynamicRAG-8B") model = AutoModelForCausalLM.from_pretrained("gasolsun/DynamicRAG-8B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add pipeline tag and library name
#1
by nielsr HF Staff - opened
This PR adds the pipeline_tag and library_name to the model card metadata. This will help users discover the model through the appropriate Hugging Face search filters. The pipeline_tag is set to question-answering based on the paper abstract which highlights the model's performance on knowledge-intensive question answering tasks.
gasolsun changed pull request status to merged