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README.md ADDED
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+
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+ ---
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+ license: apache-2.0
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+ ---
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+ # SauerkrautLM-UNA-SOLAR-Instruct
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+
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+ This is the model for SauerkrautLM-UNA-SOLAR-Instruct. I used [mergekit](https://github.com/cg123/mergekit) to merge models.
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+
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+ # Yaml Config
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+
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+ ```yaml
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+
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+ slices:
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+ - sources:
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+ - model: VAGOsolutions/SauerkrautLM-SOLAR-Instruct
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+ layer_range: [0, 48]
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+ - model: fblgit/UNA-SOLAR-10.7B-Instruct-v1.0
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+ layer_range: [0, 48]
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+
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+ merge_method: slerp
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+ base_model: upstage/SOLAR-10.7B-Instruct-v1.0
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+
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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 # fallback for rest of tensors
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+ tokenizer_source: union
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+
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+ dtype: bfloat16
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+
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+ ```
config.json ADDED
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+ {
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+ "_name_or_path": "upstage/SOLAR-10.7B-Instruct-v1.0",
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+ "architectures": [
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+ "LlamaForCausalLM"
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+ ],
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+ "attention_bias": false,
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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": 4096,
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+ "model_type": "llama",
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+ "num_attention_heads": 32,
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+ "num_hidden_layers": 48,
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+ "num_key_value_heads": 8,
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+ "pad_token_id": 2,
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+ "pretraining_tp": 1,
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+ "rms_norm_eps": 1e-05,
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+ "rope_scaling": null,
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+ "rope_theta": 10000.0,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.35.2",
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+ "use_cache": true,
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+ "vocab_size": 32000
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+ }
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