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README.md
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## Description
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FastDraft is a novel and efficient approach for pre-training and aligning a draft model to any LLM to be used with speculative decoding, by incorporating efficient pre-training followed by fine-tuning over synthetic datasets generated by the target model.
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FastDraft was presented in https://arxiv.org/abs/2411.11055 at ENLSP@NeurIPS24 by Intel Labs.
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This is a draft model that was trained with FastDraft to accompany [Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct).
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Weight compression was performed using `nncf.compress_weights` with the following parameters:
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<weight_compression>
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<all_layers value="False"/>
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<awq value="False"/>
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<group_size value="128"/>
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<ignored_scope>
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<names value="[]"/>
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<patterns value="[]"/>
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<subgraphs value="[]"/>
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<types value="[]"/>
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<validate value="True"/>
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</ignored_scope>
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<mode value="int8"/>
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<ratio value="1"/>
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<sensitivity_metric value="weight_quantization_error"/>
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</weight_compression>
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</nncf>
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For more information on quantization, check the [OpenVINO model optimization guide](https://docs.openvino.ai/2024/openvino-workflow/model-optimization-guide/weight-compression.html).
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The provided OpenVINO™ IR model is compatible with:
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* OpenVINO version
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* Optimum Intel
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## Running Model Inference with OpenVINO GenAI
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Note: run model with demo, you will need to accept license agreement.
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You must be a registered user in 🤗 Hugging Face Hub. Please visit [HuggingFace model card](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct),
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carefully read terms of usage and click accept button. You will need
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to use an access token for the code below to run. For more information
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on access tokens, refer to [this section of the documentation](https://huggingface.co/docs/hub/security-tokens).
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```
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## Disclaimer
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Intel is committed to respecting human rights and avoiding causing or contributing to adverse impacts on human rights. See [Intel’s Global Human Rights Principles](https://www.intel.com/content/dam/www/central-libraries/us/en/documents/policy-human-rights.pdf). Intel’s products and software are intended only to be used in applications that do not cause or contribute to adverse impacts on human rights.
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## Description
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FastDraft is a novel and efficient approach for pre-training and aligning a draft model to any LLM to be used with speculative decoding, by incorporating efficient pre-training followed by fine-tuning over synthetic datasets generated by the target model.
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FastDraft was presented in the [paper](https://arxiv.org/abs/2411.11055) at ENLSP@NeurIPS24 by Intel Labs.
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This is a draft model that was trained with FastDraft to accompany [Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct).
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Weight compression was performed using `nncf.compress_weights` with the following parameters:
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* mode: **INT8_ASYM**
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For more information on quantization, check the [OpenVINO model optimization guide](https://docs.openvino.ai/2024/openvino-workflow/model-optimization-guide/weight-compression.html).
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The provided OpenVINO™ IR model is compatible with:
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* OpenVINO version **2024.4** and higher
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* Optimum Intel **1.20.0** and higher
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## Running Model Inference with OpenVINO GenAI
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Note: run model with demo, you will need to accept license agreement.
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You must be a registered user in 🤗 Hugging Face Hub. Please visit [HuggingFace model card](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct),
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carefully read terms of usage and click accept button. You will need to use an access token for the code below to run. For more information
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on access tokens, refer to [this section of the documentation](https://huggingface.co/docs/hub/security-tokens).
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```
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## Disclaimer
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Intel is committed to respecting human rights and avoiding causing or contributing to adverse impacts on human rights. See [Intel’s Global Human Rights Principles](https://www.intel.com/content/dam/www/central-libraries/us/en/documents/policy-human-rights.pdf). Intel’s products and software are intended only to be used in applications that do not cause or contribute to adverse impacts on human rights.
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