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dragon-llama-answer-tool is a quantized version of DRAGON Llama 7B, with 4_K_M GGUF quantization, providing a fast, small inference implementation for use on CPUs.

dragon-llama-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-llama-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-llama-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.

Model Description

  • Developed by: llmware
  • Model type: GGUF
  • Language(s) (NLP): English
  • License: Llama 2 Community License
  • Quantized from model: llmware/dragon-llama

Model Card Contact

Darren Oberst & llmware team

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GGUF
Model size
6.74B params
Architecture
llama
Inference API
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Collection including llmware/dragon-llama-answer-tool