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Update app.py
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app.py
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@@ -2,13 +2,27 @@ import gradio as gr
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#import transformers
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#from transformers import pipeline
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from llama_cpp import Llama
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def question_answer(context, question):
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text=context + "\n\nQuestion: \"\"\"\n" + question + "\nPlease use markdown formatting for answer. \nAnswer:\n"
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llm = Llama(model_path=
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output = llm(text, max_tokens=33, stop=["### Response", "\n"], echo=True)
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print(output)
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return output.choices[0].text
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#import transformers
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#from transformers import pipeline
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from llama_cpp import Llama
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from huggingface_hub import hf_hub_download
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model_repo="TheBloke/Nous-Hermes-13B-GGML"
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model_filename="nous-hermes-13b.ggmlv3.q4_K_S.bin"
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#model="TheBloke/Nous-Hermes-13B-GGML"
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#model="https://huggingface.co/TheBloke/Nous-Hermes-13B-GGML/resolve/main/nous-hermes-13b.ggmlv3.q4_K_S.bin"
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def download_model:
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# See https://github.com/OpenAccess-AI-Collective/ggml-webui/blob/main/tabbed.py
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repo_id = hub_config.pop("repo_id")
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filename = hub_config.pop("filename")
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file = hf_hub_download(
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repo_id=model_repo, filename=model_filename
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)
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return file
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def question_answer(context, question):
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mfile=download_model()
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text=context + "\n\nQuestion: \"\"\"\n" + question + "\nPlease use markdown formatting for answer. \nAnswer:\n"
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llm = Llama(model_path=mfile)
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output = llm(text, max_tokens=33, stop=["### Response", "\n"], echo=True)
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print(output)
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return output.choices[0].text
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