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README.md

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-        <p style="margin-top: 0.5em; margin-bottom: 0em;"><a href="https://www.linkedin.com/in/david-xue-uva/">Quantized by David Xue from Astronomer</a></p>
+        <p style="margin-top: 0.5em; margin-bottom: 0em;"><a href="https://www.linkedin.com/in/david-xue-uva/">Quantized by David Xue @ Astronomer</a></p>
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 <div style="text-align:center; margin-top: 0em; margin-bottom: 0em"><p style="margin-top: 0.25em; margin-bottom: 0em;">This model is generously created and made open source by <a href="https://astronomer.io">Astronomer</p></div>
-<div style="text-align:center; margin-top: 0em; margin-bottom: 0em"><p style="margin-top: 0.25em; margin-bottom: 0em;">Astronomer is the de factor company for <a href="https://airflow.apache.org/">Apache Airflow</a>, the most trusted open-source framework for data orchestration and MLOps.</p></div>
+<div style="text-align:center; margin-top: 0em; margin-bottom: 0em"><p style="margin-top: 0.25em; margin-bottom: 0em;">Astronomer is the de facto company for <a href="https://airflow.apache.org/">Apache Airflow</a>, the most trusted open-source framework for data orchestration and MLOps.</p></div>
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 # Important Note Regarding a Known Bug in Llama 3
 - Two files are modified to address a current issue regarding Llama 3 models keep on generating additional tokens non-stop until hitting max token limit.
 - `generation_config.json`'s `eos_token_id` have been modified to add the other EOS token that Llama-3 uses.
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 ## GPTQ Quantization Method
+- This model is quantized by utilizing the AutoGPTQ library, following best practices noted by [GPTQ paper](https://arxiv.org/abs/2210.17323)
+- Quantization is calibration with random samples from the specified dataset (wikitext for now) for minimum accuracy loss.
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 | Branch | Bits | GS | Act Order | Damp % | GPTQ Dataset | Seq Len | VRAM Size | ExLlama | Desc |
 | ------ | ---- | -- | --------- | ------ | ------------ | ------- | ---- | ------- | ---- |
 | [main](https://huggingface.co/astronomer-io/Llama-3-8B-Instruct-GPTQ-8-Bit/tree/main) | 8 | 32 | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-v1/test) | 8192 | 9.09 GB | No | 8-bit, with Act Order and group size 32g. Minimum accuracy loss with decent VRAM usage reduction. |