limin(gate)
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Browse files- README.md +37 -0
- config.json +26 -0
- mergekit_config.yml +18 -0
- model-00001-of-00008.safetensors +3 -0
- model-00002-of-00008.safetensors +3 -0
- model-00003-of-00008.safetensors +3 -0
- model-00004-of-00008.safetensors +3 -0
- model-00005-of-00008.safetensors +3 -0
- model-00006-of-00008.safetensors +3 -0
- model-00007-of-00008.safetensors +3 -0
- model-00008-of-00008.safetensors +3 -0
- model.safetensors.index.json +1 -0
- special_tokens_map.json +23 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +42 -0
README.md
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---
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license: apache-2.0
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tags:
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- merge
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- mergekit
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- lazymergekit
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- liminerity/merge
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- bardsai/jaskier-7b-dpo-v5.6
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---
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# Neurotic-Jomainotrik-7b-slerp
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Neurotic-Jomainotrik-7b-slerp is a merge of the following models using [mergekit](https://github.com/cg123/mergekit):
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* [liminerity/merge](https://huggingface.co/liminerity/merge)
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* [bardsai/jaskier-7b-dpo-v5.6](https://huggingface.co/bardsai/jaskier-7b-dpo-v5.6)
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## 🧩 Configuration
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```yaml
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slices:
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- sources:
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- model: liminerity/merge
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layer_range: [0, 32]
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- model: bardsai/jaskier-7b-dpo-v5.6
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layer_range: [0, 32]
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merge_method: slerp
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base_model: liminerity/merge
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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: float16
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```
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config.json
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{
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"_name_or_path": "liminerity/merge",
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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": 10000.0,
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"sliding_window": 4096,
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"tie_word_embeddings": false,
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"torch_dtype": "float16",
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"transformers_version": "4.37.2",
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"use_cache": true,
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"vocab_size": 32000
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}
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mergekit_config.yml
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slices:
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- sources:
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- model: liminerity/merge
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layer_range: [0, 32]
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- model: bardsai/jaskier-7b-dpo-v5.6
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layer_range: [0, 32]
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merge_method: slerp
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base_model: liminerity/merge
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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: float16
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tokenizer.model
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