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README.md
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license:
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#
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<!-- Provide a quick summary of what the model is/does. -->
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**dragon-yi-
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[**dragon-yi-6b**](https://huggingface.co/llmware/dragon-yi-6b-v0) is a fact-based question-answering model, optimized for complex business documents.
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## Benchmark Tests
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To pull the model via API:
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from huggingface_hub import snapshot_download
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snapshot_download("llmware/dragon-yi-
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Load in your favorite GGUF inference engine, or try with llmware as follows:
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from llmware.models import ModelCatalog
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model = ModelCatalog().load_model("dragon-yi-
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response = model.inference(query, add_context=text_sample)
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Note: please review [**config.json**](https://huggingface.co/llmware/dragon-yi-
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### Model Description
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- **Developed by:** llmware
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- **Model type:** GGUF
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- **Language(s) (NLP):** English
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- **License:**
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## Model Card Contact
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license: apache-2.0
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inference: false
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# DRAGON-YI-9B-GGUF
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<!-- Provide a quick summary of what the model is/does. -->
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**dragon-yi-9b-gguf** is a fact-based question-answering model, optimized for complex business documents, finetuned on top of 01-ai/yi-v1.5-9b base and quantizedwith 4_K_M GGUF quantization, providing an inference implementation for use on CPUs.
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## Benchmark Tests
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To pull the model via API:
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from huggingface_hub import snapshot_download
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snapshot_download("llmware/dragon-yi-9b-gguf", local_dir="/path/on/your/machine/", local_dir_use_symlinks=False)
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Load in your favorite GGUF inference engine, or try with llmware as follows:
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from llmware.models import ModelCatalog
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model = ModelCatalog().load_model("dragon-yi-9b-gguf")
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response = model.inference(query, add_context=text_sample)
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Note: please review [**config.json**](https://huggingface.co/llmware/dragon-yi-9b-gguf/blob/main/config.json) in the repository for prompt wrapping information, details on the model, and full test set.
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### Model Description
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- **Developed by:** llmware
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- **Model type:** GGUF
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- **Language(s) (NLP):** English
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- **License:** Apache 2.0
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## Model Card Contact
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