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melino2000/tiny-llama-merge-evo-server
tiny-llama-merge-evo-server is a text generation model from melino2000. Use it when you need the model to write or continue text. It is set up for transformers.
This is a merge of pre-trained language models created using mergekit.
Downloads · 30 days
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From the Hugging Face model README
This is a merge of pre-trained language models created using mergekit.
This model was merged using the task arithmetic merge method using /home/m_nobakhtian/evol_merge_storage/input_models/TinyLlama_v1.1_684560064 as a base.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
base_model: /home/m_nobakhtian/evol_merge_storage/input_models/TinyLlama_v1.1_684560064
dtype: bfloat16
merge_method: task_arithmetic
parameters:
int8_mask: 1.0
normalize: 0.0
slices:
- sources:
- layer_range: [0, 2]
model: /home/m_nobakhtian/evol_merge_storage/input_models/TinyLlama_v1.1_chinese_1905817950
parameters:
weight: 0.9572415069321948
- layer_range: [0, 2]
model: /home/m_nobakhtian/evol_merge_storage/input_models/TinyLlama_v1.1_684560064
- sources:
- layer_range: [2, 4]
model: /home/m_nobakhtian/evol_merge_storage/input_models/TinyLlama_v1.1_chinese_1905817950
parameters:
weight: 1.3027552693206474
- layer_range: [2, 4]
model: /home/m_nobakhtian/evol_merge_storage/input_models/TinyLlama_v1.1_684560064
- sources:
- layer_range: [4, 6]
model: /home/m_nobakhtian/evol_merge_storage/input_models/TinyLlama_v1.1_chinese_1905817950
parameters:
weight: 1.1000872891940183
- layer_range: [4, 6]
model: /home/m_nobakhtian/evol_merge_storage/input_models/TinyLlama_v1.1_684560064
- sources:
- layer_range: [6, 8]
model: /home/m_nobakhtian/evol_merge_storage/input_models/TinyLlama_v1.1_chinese_1905817950
parameters:
weight: 0.8472430654902018
- layer_range: [6, 8]
model: /home/m_nobakhtian/evol_merge_storage/input_models/TinyLlama_v1.1_684560064
- sources:
- layer_range: [8, 10]
model: /home/m_nobakhtian/evol_merge_storage/input_models/TinyLlama_v1.1_chinese_1905817950
parameters:
weight: 0.9915310236895785
- layer_range: [8, 10]
model: /home/m_nobakhtian/evol_merge_storage/input_models/TinyLlama_v1.1_684560064
- sources:
- layer_range: [10, 12]
model: /home/m_nobakhtian/evol_merge_storage/input_models/TinyLlama_v1.1_chinese_1905817950
parameters:
weight: 1.1144858726152178
- layer_range: [10, 12]
model: /home/m_nobakhtian/evol_merge_storage/input_models/TinyLlama_v1.1_684560064
- sources:
- layer_range: [12, 14]
model: /home/m_nobakhtian/evol_merge_storage/input_models/TinyLlama_v1.1_chinese_1905817950
parameters:
weight: 0.8140779929520541
- layer_range: [12, 14]
model: /home/m_nobakhtian/evol_merge_storage/input_models/TinyLlama_v1.1_684560064
- sources:
- layer_range: [14, 16]
model: /home/m_nobakhtian/evol_merge_storage/input_models/TinyLlama_v1.1_chinese_1905817950
parameters:
weight: 1.1599951316231072
- layer_range: [14, 16]
model: /home/m_nobakhtian/evol_merge_storage/input_models/TinyLlama_v1.1_684560064
- sources:
- layer_range: [16, 18]
model: /home/m_nobakhtian/evol_merge_storage/input_models/TinyLlama_v1.1_chinese_1905817950
parameters:
weight: 0.5993074778392211
- layer_range: [16, 18]
model: /home/m_nobakhtian/evol_merge_storage/input_models/TinyLlama_v1.1_684560064
- sources:
- layer_range: [18, 20]
model: /home/m_nobakhtian/evol_merge_storage/input_models/TinyLlama_v1.1_chinese_1905817950
parameters:
weight: 0.8145134707653817
- layer_range: [18, 20]
model: /home/m_nobakhtian/evol_merge_storage/input_models/TinyLlama_v1.1_684560064
- sources:
- layer_range: [20, 22]
model: /home/m_nobakhtian/evol_merge_storage/input_models/TinyLlama_v1.1_chinese_1905817950
parameters:
weight: 0.9579703282891905
- layer_range: [20, 22]
model: /home/m_nobakhtian/evol_merge_storage/input_models/TinyLlama_v1.1_684560064