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README.md
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<p>This is my first foray into 70b models, so this is more or less an experiment, please let me know your thoughts on the model and where their can be improvements.<br>
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L3-MS-Astoria-70b combines the strengths of multiple models to deliver a well-rounded, capable assistant. It is aimed at performing general tasks, storytelling, roleplay, and more mature content.<br>
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The model stock merging method attempts to make the model remain focused, tailored, and high-quality.
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<h2>
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<pre><code>MODEL_NAME = "L3-MS-Astoria-70b"
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yaml_config = """
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base_model: failspy/llama-3-70B-Instruct-abliterated
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- model: NeverSleep/Llama-3-Lumimaid-70B-v0.1-alt
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"""
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</code></pre>
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<p><strong>migtissera/Tess-2.0-Llama-3-70B-v0.2:</strong><br>
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Tess, short for Tesoro (Treasure in Italian), is a general purpose Large Language Model series. Tess-2.0-Llama-3-70B-v0.2 was trained on the meta-llama/Meta-Llama-3-70B base. The change between v0.1 and this version, v0.2 is that v0.2 has undergone an additional step of uncensoring.
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</p>
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<p>This is my first foray into 70b models, so this is more or less an experiment, please let me know your thoughts on the model and where their can be improvements.<br>
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L3-MS-Astoria-70b combines the strengths of multiple models to deliver a well-rounded, capable assistant. It is aimed at performing general tasks, storytelling, roleplay, and more mature content.<br>
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The model stock merging method attempts to make the model remain focused, tailored, and high-quality.
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<h2>Quants:</h2>
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<p>(Thanks to <a href="https://huggingface.co/mradermacher">@Mradermacher!</a>, please send them likes and follows!)</p>
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<p><a href="https://huggingface.co/mradermacher/L3-MS-Astoria-70b-GGUF">L3-Arcania-4x8b-GGUF (GGUFs)</a></p>
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<p></p>
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<h3>Config:</h3>
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<pre><code>MODEL_NAME = "L3-MS-Astoria-70b"
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yaml_config = """
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base_model: failspy/llama-3-70B-Instruct-abliterated
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- model: NeverSleep/Llama-3-Lumimaid-70B-v0.1-alt
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"""
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</code></pre>
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<h4>Source Model Details:</h4>
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<p><strong>migtissera/Tess-2.0-Llama-3-70B-v0.2:</strong><br>
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Tess, short for Tesoro (Treasure in Italian), is a general purpose Large Language Model series. Tess-2.0-Llama-3-70B-v0.2 was trained on the meta-llama/Meta-Llama-3-70B base. The change between v0.1 and this version, v0.2 is that v0.2 has undergone an additional step of uncensoring.
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</p>
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