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- README.md +38 -0
- config.json +30 -0
- mergekit_config.yml +16 -0
- merges.txt +0 -0
- model-00001-of-00082.safetensors +3 -0
- model-00002-of-00082.safetensors +3 -0
- model-00003-of-00082.safetensors +3 -0
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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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- mistralai/Mistral-7B-v0.1+predibase/customer_support
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- NousResearch/Nous-Hermes-2-Mistral-7B-DPO
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---
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# Mistral-Hermes-Support-Ties
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Mistral-Hermes-Support-Ties is a merge of the following models using [mergekit](https://github.com/cg123/mergekit):
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* [mistralai/Mistral-7B-v0.1+predibase/customer_support](https://huggingface.co/mistralai/Mistral-7B-v0.1+predibase/customer_support)
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* [NousResearch/Nous-Hermes-2-Mistral-7B-DPO](https://huggingface.co/NousResearch/Nous-Hermes-2-Mistral-7B-DPO)
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## 🧩 Configuration
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```yaml
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models:
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- model: mistralai/Mistral-7B-Instruct-v0.2
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#no parameters necessary for base model
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- model: mistralai/Mistral-7B-v0.1+predibase/customer_support
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parameters:
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density: 0.5
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weight: 0.5
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- model: NousResearch/Nous-Hermes-2-Mistral-7B-DPO
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parameters:
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density: 0.5
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weight: 0.5
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merge_method: ties
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base_model: mistralai/Mistral-7B-Instruct-v0.2
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parameters:
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normalize: false
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int8_mask: true
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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": "abacusai/Smaug-72B-v0.1",
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": true,
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 151643,
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"hidden_act": "silu",
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"hidden_size": 8192,
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"initializer_range": 0.02,
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"intermediate_size": 24576,
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"max_position_embeddings": 32768,
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"model_type": "llama",
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"num_attention_heads": 64,
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"num_hidden_layers": 80,
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"num_key_value_heads": 64,
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"pad_token_id": 151643,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-06,
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"rope_scaling": null,
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"rope_theta": 1000000,
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"seq_length": 32768,
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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": true,
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"vocab_size": 152064
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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: ibivibiv/alpaca-dragon-72b-v1
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layer_range: [0, 80]
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- model: abacusai/Smaug-72B-v0.1
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layer_range: [0, 80]
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merge_method: slerp
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base_model: abacusai/Smaug-72B-v0.1
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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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merges.txt
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