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update readme.md

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@@ -20,7 +20,7 @@ Waxwing is a storytelling lora for Llama 2 70B.
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  - Tailor the feel of your story using style tags.
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  - Experience storytelling free of ChatGPT's idiosyncrasies, thanks to a "human-generated" dataset of public domain writing. Waxwing avoids GPT-isms like positivity bias, "bond" emphasis, rushed endings and exaggerated stylistic tics.
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- Waxwing is available:
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  - LoRA: As a LoRA on this branch and can be applied at runtime on any variant of the Llama 2 70B base model.
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  - 16fp model: Merged into the base Llama 2 model, in full precision in the [16fp](https://huggingface.co/alac/Waxwing-Storytelling-70B-LoRA/tree/16fp) branch.
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  - Quantized for used with Exllama 2:
@@ -29,6 +29,7 @@ Waxwing is available:
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  - [4.65bpw](https://huggingface.co/alac/Waxwing-Storytelling-70B-LoRA/tree/4.65bpw)
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  - [6.0bpw](https://huggingface.co/alac/Waxwing-Storytelling-70B-LoRA/tree/6.0bpw)
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  - [8.0bpw](https://huggingface.co/alac/Waxwing-Storytelling-70B-LoRA/tree/8.0bpw)
 
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  By using this model, you take full responsibility for anything done with its outputs.
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  - Tailor the feel of your story using style tags.
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  - Experience storytelling free of ChatGPT's idiosyncrasies, thanks to a "human-generated" dataset of public domain writing. Waxwing avoids GPT-isms like positivity bias, "bond" emphasis, rushed endings and exaggerated stylistic tics.
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+ Waxwing is available*:
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  - LoRA: As a LoRA on this branch and can be applied at runtime on any variant of the Llama 2 70B base model.
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  - 16fp model: Merged into the base Llama 2 model, in full precision in the [16fp](https://huggingface.co/alac/Waxwing-Storytelling-70B-LoRA/tree/16fp) branch.
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  - Quantized for used with Exllama 2:
 
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  - [4.65bpw](https://huggingface.co/alac/Waxwing-Storytelling-70B-LoRA/tree/4.65bpw)
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  - [6.0bpw](https://huggingface.co/alac/Waxwing-Storytelling-70B-LoRA/tree/6.0bpw)
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  - [8.0bpw](https://huggingface.co/alac/Waxwing-Storytelling-70B-LoRA/tree/8.0bpw)
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+ *this is something like 400gb of model, so it might take a while to upload.
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  By using this model, you take full responsibility for anything done with its outputs.
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