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license: apache-2.0 |
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# SLIM-QA-GEN-PHI-3-TOOL |
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<!-- Provide a quick summary of what the model is/does. --> |
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**slim-qa-gen-phi-3-tool** is a 4_K_M quantized GGUF version of slim-qa-gen-phi-3, providing a small, fast inference implementation, optimized for multi-model concurrent deployment. |
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This model implements a generative 'question' and 'answer' (e.g., 'qa-gen') function, which takes a context passage as an input, and then generates as an output a python dictionary consisting of two keys: |
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`{'question': ['What was the amount of revenue in the quarter?'], 'answer': ['$3.2 billion']} ` |
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The model has been designed to accept one of three different parameters to guide the type of question-answer created: |
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-- 'question, answer' (generates a standard question and answer), |
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-- 'boolean' (generates a 'yes-no' question and answer), and |
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-- 'multiple choice' (generates a multiple choice question and answer). |
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Note: we would generally recommend using sampling and temperature(0.5+) for varied generations, although if using 'multiple choice' mode, then we have seen the best results with temperature in the 0.2-0.3 range. |
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[**slim-qa-gen-phi-3**](https://huggingface.co/llmware/slim-qa-gen-phi-3) is the Pytorch version of the model, and suitable for fine-tuning for further domain adaptation. |
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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/slim-qa-gen-phi-3-tool", 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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# to load the model and make a basic inference |
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model = ModelCatalog().load_model("slim-qa-gen-phi-3-tool", temperature=0.5, sample=True) |
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response = model.function_call(text_sample, params=["boolean"]) |
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# this one line will download the model and run a series of tests |
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ModelCatalog().tool_test_run("slim-qa-gen-phi-3-tool", verbose=True) |
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Note: please review [**config.json**](https://huggingface.co/llmware/slim-qa-gen-phi-3-tool/blob/main/config.json) in the repository for prompt template information, details on the model, and full test set. |
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## Model Card Contact |
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Darren Oberst & llmware team |
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[Any questions? Join us on Discord](https://discord.gg/MhZn5Nc39h) |
