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README.md
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<h2 style="font-size:20px; font-weight:600; ">Provided Files:</h2>
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<p style="font-size:18px; margin-top:12px"><b><a style="text-decoration:none" href="https://huggingface.co/CONCISE/LLaMa_V2-13B-Instruct-Uncensored-GGML/blob/main/LLaMa_V2-13B-Instruct-Uncensored-f16-Unquantized-GGML.bin">LLaMa_V2-13B-Instruct-Uncensored-f16-Unquantized-GGML.bin</a></b></p>
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<br> <br> <br><br> <br> <br>
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<h1 style="font-size:20px;margin-bottom:35px">
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Quantized LLaMa.V2 13B model weights - Instruction based
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<p style="font-size:18px;">
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Big thank you to Eric Hartford for his work aiding the creation of datasets such as:<br>
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-</span> wizardlm_evol_instruct_V2_196k_unfiltered_merged_split<br>
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<span style="font-size:22px; font-weight:bold;margin-left:10px; margin-right:5px">
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-</span> wizard_vicuna_70k_unfiltered<br>
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Such datasets play a big role in accurately addressing model biases, without sacrificing performance
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</p>
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<div style="height: 1px; background-color:#666; margin: 30px 0 -5px 0; width:100%"></div>
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<h2 style="font-size:20px; font-weight:600; ">Provided Files:</h2>
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<p style="font-size:18px; margin-top:12px"><b><a style="text-decoration:none" href="https://huggingface.co/CONCISE/LLaMa_V2-13B-Instruct-Uncensored-GGML/blob/main/LLaMa_V2-13B-Instruct-Uncensored-f16-Unquantized-GGML.bin">LLaMa_V2-13B-Instruct-Uncensored-f16-Unquantized-GGML.bin</a></b></p>
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<br> <br>
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