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Browse files- README.md +36 -0
- config.json +28 -0
- mergekit_config.yml +17 -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 +30 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +43 -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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- OpenPipe/mistral-ft-optimized-1218
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- mlabonne/NeuralHermes-2.5-Mistral-7B
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---
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# SFGEMOMNISCIEN-Mistral-ties
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SFGEMOMNISCIEN-Mistral-ties is a merge of the following models using mergekit:
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* [OpenPipe/mistral-ft-optimized-1218](https://huggingface.co/OpenPipe/mistral-ft-optimized-1218)
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* [mlabonne/NeuralHermes-2.5-Mistral-7B](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B)
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## 🧩 Configuration
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\```yaml
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models:
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- model: Warit2/SFGEMOMNISCIEN
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# no parameters necessary for base model
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- model: OpenPipe/mistral-ft-optimized-1218
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parameters:
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density: 0.5
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weight: 0.5
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- model: mlabonne/NeuralHermes-2.5-Mistral-7B
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parameters:
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density: 0.5
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weight: 0.3
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merge_method: ties
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base_model: Warit2/SFGEMOMNISCIEN
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parameters:
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normalize: 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": "Warit2/SFGEMOMNISCIEN",
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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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"pad_token_id": 2,
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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": "4.39.3",
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"unsloth_version": "2024.3",
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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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models:
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- model: Warit2/SFGEMOMNISCIEN
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# no parameters necessary for base model
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- model: OpenPipe/mistral-ft-optimized-1218
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parameters:
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density: 0.5
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weight: 0.5
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- model: mlabonne/NeuralHermes-2.5-Mistral-7B
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parameters:
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density: 0.5
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weight: 0.3
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merge_method: ties
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base_model: Warit2/SFGEMOMNISCIEN
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parameters:
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normalize: true
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dtype: float16
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model-00001-of-00008.safetensors
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tokenizer.model
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"sp_model_kwargs": {},
|
39 |
+
"spaces_between_special_tokens": false,
|
40 |
+
"tokenizer_class": "LlamaTokenizer",
|
41 |
+
"unk_token": "<unk>",
|
42 |
+
"use_default_system_prompt": false
|
43 |
+
}
|