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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
README.md ADDED
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+ ---
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+ library_name: transformers
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+ base_model:
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+ - Nitral-AI/Captain-Eris_Violet-V0.420-12B
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+ ---
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/642265bc01c62c1e4102dc36/V4OFnx7IBvXhYphdkUr5F.png)
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+
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+ # Captain-Eris_Violet-V0.420-12B-6bpw-h8-exl2
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+
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+ This is a 6bpw h8 exl2 quant of [Captain-Eris_Violet-V0.420-12B](https://huggingface.co/Nitral-AI/Captain-Eris_Violet-V0.420-12B)
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+
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+ Built-in(default) calibration dataset is used.
config.json ADDED
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+ {
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+ "_name_or_path": "Captain-Eris_Violet-V0.420-12B-6bpw-h8-exl2",
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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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+ "head_dim": 128,
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+ "hidden_act": "silu",
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+ "hidden_size": 5120,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 14336,
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+ "max_position_embeddings": 1024000,
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+ "model_type": "mistral",
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+ "num_attention_heads": 32,
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+ "num_hidden_layers": 40,
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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": "4.46.2",
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+ "use_cache": true,
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+ "vocab_size": 131072,
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+ "quantization_config": {
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+ "quant_method": "exl2",
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+ "version": "0.2.6",
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+ "bits": 6.0,
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+ "head_bits": 8,
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+ "calibration": {
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+ "rows": 115,
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+ "length": 2048,
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+ "dataset": "(default)"
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+ }
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+ }
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+ }
measurement.json ADDED
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mergekit_config.yml ADDED
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+ slices:
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+ - sources:
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+ - model: Nitral-AI/Captain_BMO-12B
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+ layer_range: [0, 40]
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+ - model: Epiculous/Violet_Twilight-v0.2
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+ layer_range: [0, 40]
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+ merge_method: slerp
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+ base_model: Nitral-AI/Captain_BMO-12B
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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: 0.420
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+ dtype: bfloat16
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