merged
Use v1!
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the passthrough merge method.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
dtype: bfloat16
merge_method: passthrough
slices:
- sources:
- layer_range: [0, 8]
model: nvidia/Mistral-NeMo-Minitron-8B-Base
- sources:
- layer_range: [8, 16]
model: nvidia/Mistral-NeMo-Minitron-8B-Base
parameters:
scale:
- filter: input_layernorm
value: 0.75
- value: 1.0
- sources:
- layer_range: [8, 16]
model: nvidia/Mistral-NeMo-Minitron-8B-Base
parameters:
scale:
- filter: input_layernorm
value: 0.75
- filter: v_proj
value: 0.5
- filter: post_attention_layernorm
value: 0.5
- value: 1.0
- sources:
- layer_range: [16, 17]
model: nvidia/Mistral-NeMo-Minitron-8B-Base
- sources:
- layer_range: [17, 24]
model: nvidia/Mistral-NeMo-Minitron-8B-Base
parameters:
scale:
- filter: input_layernorm
value: 0.75
- value: 1.0
- sources:
- layer_range: [17, 24]
model: nvidia/Mistral-NeMo-Minitron-8B-Base
parameters:
scale:
- filter: input_layernorm
value: 0.75
- filter: v_proj
value: 0.5
- filter: post_attention_layernorm
value: 0.5
- value: 1.0
- sources:
- layer_range: [24, 25]
model: nvidia/Mistral-NeMo-Minitron-8B-Base
- sources:
- layer_range: [25, 32]
model: nvidia/Mistral-NeMo-Minitron-8B-Base
parameters:
scale:
- filter: input_layernorm
value: 0.75
- filter: v_proj
value: 0.5
- filter: post_attention_layernorm
value: 0.5
- value: 1.0
- sources:
- layer_range: [25, 40]
model: nvidia/Mistral-NeMo-Minitron-8B-Base
- Downloads last month
- 12
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.