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README.md ADDED
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+ ---
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+ base_model:
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+ - Nitral-AI/Lewcules-7B-v.02
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+ - l3utterfly/mistral-7b-v0.2-layla-v4
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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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+ ---
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+ # mergedmodel
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+
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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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+
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+ ## Merge Details
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+ ### Merge Method
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+
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+ This model was merged using the SLERP merge method.
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+
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+ ### Models Merged
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+
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+ The following models were included in the merge:
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+ * [Nitral-AI/Lewcules-7B-v.02](https://huggingface.co/Nitral-AI/Lewcules-7B-v.02)
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+ * [l3utterfly/mistral-7b-v0.2-layla-v4](https://huggingface.co/l3utterfly/mistral-7b-v0.2-layla-v4)
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+
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+ ### Configuration
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+
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+ The following YAML configuration was used to produce this model:
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+
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+ ```yaml
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+ slices:
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+ - sources:
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+ - model: Nitral-AI/Lewcules-7B-v.02
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+ layer_range: [0, 32]
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+ - model: l3utterfly/mistral-7b-v0.2-layla-v4
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+ layer_range: [0, 32]
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+ merge_method: slerp
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+ base_model: Nitral-AI/Lewcules-7B-v.02
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+ parameters:
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+ t:
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+ - filter: self_attn
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+ value: [0, 0.5, 0.3, 0.7, 1]
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+ - filter: mlp
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+ value: [1, 0.5, 0.7, 0.3, 0]
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+ - value: 0.5
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+ dtype: bfloat16
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+ ```
config.json ADDED
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+ {
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+ "_name_or_path": "Nitral-AI/Lewcules-7B-v.02",
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+ "architectures": [
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+ "MistralForCausalLM"
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+ ],
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+ "attention_dropout": 0.0,
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+ "bos_token_id": 1,
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+ "eos_token_id": 2,
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+ "hidden_act": "silu",
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+ "hidden_size": 4096,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 14336,
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+ "max_position_embeddings": 32768,
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+ "model_type": "mistral",
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+ "num_attention_heads": 32,
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+ "num_hidden_layers": 32,
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+ "num_key_value_heads": 8,
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+ "rms_norm_eps": 1e-05,
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+ "rope_theta": 1000000.0,
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+ "sliding_window": null,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.38.2",
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+ "use_cache": false,
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+ "vocab_size": 32000
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+ }
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+ slices:
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+ - sources:
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+ - model: Nitral-AI/Lewcules-7B-v.02
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+ layer_range: [0, 32]
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+ - model: l3utterfly/mistral-7b-v0.2-layla-v4
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+ layer_range: [0, 32]
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+ merge_method: slerp
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+ base_model: Nitral-AI/Lewcules-7B-v.02
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+ parameters:
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+ t:
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+ - filter: self_attn
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+ value: [0, 0.5, 0.3, 0.7, 1]
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+ - filter: mlp
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+ value: [1, 0.5, 0.7, 0.3, 0]
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+ - value: 0.5
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+ dtype: bfloat16
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