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README.md
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---
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base_model:
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- defog/llama-3-sqlcoder-8b
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- meta-llama/Meta-Llama-3-8B-Instruct
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library_name: transformers
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tags:
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- mergekit
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- merge
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---
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# QuantFactory/sepctrum-ties-sqlcoder-8b-GGUF
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This is quantized version of [arcee-ai/sepctrum-ties-sqlcoder-8b](https://huggingface.co/arcee-ai/sepctrum-ties-sqlcoder-8b) created using llama.cpp
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# Original Model Card
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# merge
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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## Merge Details
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### Merge Method
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This model was merged using the [TIES](https://arxiv.org/abs/2306.01708) merge method using [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) as a base.
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### Models Merged
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The following models were included in the merge:
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* [defog/llama-3-sqlcoder-8b](https://huggingface.co/defog/llama-3-sqlcoder-8b)
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### Configuration
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The following YAML configuration was used to produce this model:
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```yaml
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merge_method: ties
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base_model: meta-llama/Meta-Llama-3-8B-Instruct
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models:
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- model: defog/llama-3-sqlcoder-8b
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parameters:
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weight:
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- filter: mlp.down_proj
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value: [0, 0, 0, 0, 0, 0, 0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0, 0.5, 0, 0, 0, 0, 0, 0.5, 0.5, 0.5, 0.5, 0.5, 0, 0, 0]
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- filter: mlp.gate_proj
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value: [0, 0, 0, 0, 0, 0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0.5]
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- filter: mlp.up_proj
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value: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0.5, 0, 0, 0, 0, 0.5, 0, 0.5, 0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5]
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- filter: self_attn.k_proj
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value: [0.5, 0.5, 0.5, 0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0, 0.5, 0.5, 0.5, 0.5, 0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0]
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- filter: self_attn.o_proj
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value: [0.5, 0.5, 0.5, 0.5, 0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0.5, 0.5, 0.5, 0.5, 0, 0.5, 0, 0, 0, 0.5, 0.5, 0.5, 0.5, 0.5, 0]
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- filter: self_attn.q_proj
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value: [0, 0, 0.5, 0.5, 0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0, 0.5, 0.5, 0.5, 0.5, 0.5]
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- filter: self_attn.v_proj
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value: [0.5, 0, 0.5, 0, 0, 0.5, 0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0, 0, 0, 0, 0.5, 0.5, 0, 0, 0, 0, 0.5, 0, 0, 0.5, 0, 0, 0.5, 0.5]
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- value: [0]
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density: 0.75
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- model: meta-llama/Meta-Llama-3-8B-Instruct
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parameters:
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weight:
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- filter: mlp.down_proj
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value: [1, 1, 1, 1, 1, 1, 1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 1, 0.5, 1, 1, 1, 1, 1, 0.5, 0.5, 0.5, 0.5, 0.5, 1, 1, 1]
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- filter: mlp.gate_proj
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value: [1, 1, 1, 1, 1, 1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.5, 0.5]
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- filter: mlp.up_proj
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value: [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.5, 0.5, 1, 1, 1, 1, 0.5, 1, 0.5, 1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5]
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- filter: self_attn.k_proj
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value: [0.5, 0.5, 0.5, 1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 1, 0.5, 0.5, 0.5, 0.5, 0.5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.5, 1]
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- filter: self_attn.o_proj
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value: [0.5, 0.5, 0.5, 0.5, 0.5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.5, 0.5, 0.5, 0.5, 0.5, 1, 0.5, 1, 1, 1, 0.5, 0.5, 0.5, 0.5, 0.5, 1]
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- filter: self_attn.q_proj
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value: [1, 1, 0.5, 0.5, 0.5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 1, 0.5, 0.5, 0.5, 0.5, 0.5]
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- filter: self_attn.v_proj
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value: [0.5, 1, 0.5, 1, 1, 0.5, 1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 1, 1, 1, 1, 0.5, 0.5, 1, 1, 1, 1, 0.5, 1, 1, 0.5, 1, 1, 0.5, 0.5]
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- value: [1]
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density: 1.0
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parameters: {normalize: true, int8_mask: true}
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dtype: bfloat16
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```
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