DRAGON Models
					Collection
				
Production-grade RAG-optimized 6-7B parameter models - "Delivering RAG on ..." the leading foundation base models
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				23 items
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dragon-mistral-answer-tool is a quantized version of DRAGON Mistral 7B, with 4_K_M GGUF quantization, providing a fast, small inference implementation for use on CPUs.
dragon-mistral-7b is a fact-based question-answering model, optimized for complex business documents.
To pull the model via API:
from huggingface_hub import snapshot_download           
snapshot_download("llmware/dragon-mistral-answer-tool", local_dir="/path/on/your/machine/", local_dir_use_symlinks=False)  
Load in your favorite GGUF inference engine, or try with llmware as follows:
from llmware.models import ModelCatalog  
model = ModelCatalog().load_model("dragon-mistral-answer-tool")            
response = model.inference(query, add_context=text_sample)  
Note: please review config.json in the repository for prompt wrapping information, details on the model, and full test set.
Darren Oberst & llmware team
We're not able to determine the quantization variants.