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README.md
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---
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license: apache-2.0
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---
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license: apache-2.0
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base_model:
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- nvidia/Mistral-NeMo-Minitron-8B-Instruct
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tags:
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- OpenArc
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- OpenVINO
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- Intel
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---
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My Project [OpenArc](https://github.com/SearchSavior/OpenArc), an inference engine for OpenVINO, now supports this model and serves inference over OpenAI compatible endpoints for text to text *and* text with vision!
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We have a growing Discord community of others interested in using Intel for AI/ML.
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[](https://discord.gg/maMY7QjG)
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- Find documentation on the Optimum-CLI export process [here](https://huggingface.co/docs/optimum/main/en/intel/openvino/export)
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- Use my HF space [Echo9Zulu/Optimum-CLI-Tool_tool](https://huggingface.co/spaces/Echo9Zulu/Optimum-CLI-Tool_tool) to build commands and execute locally
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## This repo contains OpenVINO quantizations of nvidia/Mistral-NeMo-Minitron-8B-Instruct.
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I reccomend starting with **Mistral-NeMo-Minitron-8B-Instruct-int4_asym-awq-se-ov**
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To download individual models from this repo use the provided snippet:
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```
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from huggingface_hub import snapshot_download
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repo_id = "Echo9Zulu/Mistral-NeMo-Minitron-8B-Instruct-OpenVINO"
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# Choose the weights you want
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repo_directory = "Mistral-NeMo-Minitron-8B-Instruct-int4_asym-awq-se-ov"
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# Where you want to save it
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local_dir = "./Echo9Zulu_Mistral-NeMo-Minitron-8B-Instruct/Mistral-NeMo-Minitron-8B-Instruct-int4_asym-awq-se-ov"
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snapshot_download(
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repo_id=repo_id,
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allow_patterns=[f"{repo_directory}/*"],
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local_dir=local_dir,
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local_dir_use_symlinks=True
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)
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print("Download complete!")
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```
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