Edit model card

GemOmniscien-ties

GemOmniscien-ties is a merge of the following models using mergekit:

🧩 Configuration

```yaml models:

  • model: Warit2/GemOmniscien parameters: density: 0.5 weight: 0.5
  • model: google/gemma-2b-it parameters: density: 0.5 weight: 0.5 # weight gradient merge_method: ties base_model: Warit2/GemOmniscien parameters: normalize: true int8_mask: true dtype: bfloat16

models:

- model: unsloth/gemma-7b-bnb-4bit

layer_range: [0, 32]

# no parameters necessary for base model

- model: mistralai/Mistral-7B-v0.1

layer_range: [24, 32]

merge_method: passthrough

# base_model: unsloth/gemma-7b-bnb-4bit

parameters:

normalize: true

int8_mask: true

dtype: float16

slices:

- sources:

- model: unsloth/gemma-2b-bnb-4bit

layer_range: [0, 16]

- sources:

- model: NousResearch/Nous-Hermes-llama-2-7b

layer_range: [0, 22]

merge_method: passthrough

dtype: bfloat16

models:

- model: unsloth/gemma-2b-bnb-4bit

parameters:

density: 0.53

weight: 0.45

- model: TinyLlama/TinyLlama-1.1B-Chat-v1.0

parameters:

weight: 0.5

merge_method: ties

base_model: unsloth/gemma-2b-bnb-4bit

parameters:

int8_mask: true

dtype: bfloat16

```

Downloads last month
5
Safetensors
Model size
2.51B params
Tensor type
BF16
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.