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See https://github.com/qualcomm/ai-hub-models/releases/v0.62.2 for changelog.

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  1. README.md +3 -3
README.md CHANGED
@@ -16,7 +16,7 @@ pipeline_tag: text-generation
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  Falcon3 family of Open Foundation Models is a set of pretrained and instruct LLMs ranging from 1B to 10B.
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  This is based on the implementation of Falcon3-7B-Instruct found [here](https://huggingface.co/tiiuae/Falcon3-7B-Instruct).
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- This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.62.1/src/qai_hub_models/models/falcon_v3_7b_instruct) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).
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  Qualcomm AI Hub Models uses [Qualcomm AI Hub Workbench](https://workbench.aihub.qualcomm.com) to compile, profile, and evaluate this model. [Sign up](https://myaccount.qualcomm.com/signup) to run these models on a hosted Qualcomm® device.
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@@ -30,12 +30,12 @@ See the [LLM-on-Genie](https://github.com/qualcomm/ai-hub-apps/tree/main/tutoria
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  ## Getting Started
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  Due to licensing restrictions, we cannot distribute pre-exported model assets for this model.
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- Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.62.1/src/qai_hub_models/models/falcon_v3_7b_instruct) Python library to compile and export the model with your own:
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  - Custom weights (e.g., fine-tuned checkpoints)
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  - Custom input shapes
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  - Target device and runtime configurations
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- See our repository for [Falcon3-7B-Instruct on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.62.1/src/qai_hub_models/models/falcon_v3_7b_instruct) for usage instructions.
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  ## Model Details
 
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  Falcon3 family of Open Foundation Models is a set of pretrained and instruct LLMs ranging from 1B to 10B.
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  This is based on the implementation of Falcon3-7B-Instruct found [here](https://huggingface.co/tiiuae/Falcon3-7B-Instruct).
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+ This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.62.2/src/qai_hub_models/models/falcon_v3_7b_instruct) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).
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  Qualcomm AI Hub Models uses [Qualcomm AI Hub Workbench](https://workbench.aihub.qualcomm.com) to compile, profile, and evaluate this model. [Sign up](https://myaccount.qualcomm.com/signup) to run these models on a hosted Qualcomm® device.
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  ## Getting Started
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  Due to licensing restrictions, we cannot distribute pre-exported model assets for this model.
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+ Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.62.2/src/qai_hub_models/models/falcon_v3_7b_instruct) Python library to compile and export the model with your own:
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  - Custom weights (e.g., fine-tuned checkpoints)
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  - Custom input shapes
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  - Target device and runtime configurations
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+ See our repository for [Falcon3-7B-Instruct on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.62.2/src/qai_hub_models/models/falcon_v3_7b_instruct) for usage instructions.
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  ## Model Details