A merged model of [Mediform/mistral_gml_7b](https://huggingface.co/Mediform/mistral_gml_7b), [AIDC-ai-business/Marcoroni-7B-v3](https://huggingface.co/AIDC-ai-business/Marcoroni-7B-v3), and [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) using [SLERP merge](https://github.com/cg123/mergekit).

The merging consists of two stages:
1. Merge `mistral_gml_7b` with `Marcoroni-7B-v3`, resulting `GMarc` model. The config is as follows:
   
```yaml
slices:
  - sources:
      - model: Mediform/mistral_gml_7b
        layer_range: [0, 32]
      - model: AIDC-ai-business/Marcoroni-7B-v3
        layer_range: [0, 32]
merge_method: slerp
base_model: Mediform/mistral_gml_7b
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5 # fallback for rest of tensors
dtype: bfloat16

```
2. Merge the resulting model with `OpenHermes-2.5-Mistral-7B`:
 ```yaml
slices:
  - sources:
      - model: /workspace/data/anhnv79/GMarc
        layer_range: [0, 32]
      - model: teknium/OpenHermes-2.5-Mistral-7B
        layer_range: [0, 32]
merge_method: slerp
base_model: /workspace/data/anhnv79/GMarc
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5 # fallback for rest of tensors
dtype: bfloat16

```

{}
transformers safetensors mistral text-generation autotrain_compatible endpoints_compatible text-generation-inference region:us